huggingartists-demo.ipynb

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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TVqWHLWBSv8v"
      },
      "source": [
        "# HuggingArtists - Train a model to generate lyrics\n",
        "\n",
        "Choose your favorite Artist and train a language model to write new lyrics based on their unique voice in just 5 minutes.\n",
        "\n",
        "Auto-continue training from last chechpoint from [Hub](https://huggingface.co/huggingartists).\n",
        "\n",
        "[![GitHub stars](https://img.shields.io/github/stars/AlekseyKorshuk/huggingartists?style=social)](https://github.com/AlekseyKorshuk/huggingartists)\n",
        "\n",
        "<img src=\"https://raw.githubusercontent.com/AlekseyKorshuk/huggingartists/master/img/logo.jpg\" width=\"520\" align=\"center\">"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "R4KG9ERHV2Eq"
      },
      "source": [
        "## How to use\n",
        "\n",
        "To start the demo, click on menu at top, \"Runtime\" → \"Run all\" or \"Ctrl\" + \"F9\".\n",
        "\n",
        "Contact me if something doesn't work: [link](https://github.com/AlekseyKorshuk).\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rfyl8xdLz8ZW",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "cellView": "form",
        "outputId": "df59677c-7f38-4020-bd20-6a6ce7488a72"
      },
      "source": [
        "#@title Settings\n",
        "#@markdown Enter artist name:\n",
        "artist_name = \"Eminem\" #@param {type:\"string\"}\n",
        "#@markdown Check existing dataset first (it will save 1-2 min but will not add new songs):\n",
        "check_dataset = True #@param {type:\"boolean\"} \n",
        "#@markdown Total number of training epochs to perform (more epochs -> better result -> more time):\n",
        "num_train_epochs =  1#@param {type:\"integer\"}\n",
        "!nvidia-smi"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Tue Aug 17 19:07:59 2021       \n",
            "+-----------------------------------------------------------------------------+\n",
            "| NVIDIA-SMI 470.57.02    Driver Version: 460.32.03    CUDA Version: 11.2     |\n",
            "|-------------------------------+----------------------+----------------------+\n",
            "| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
            "| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n",
            "|                               |                      |               MIG M. |\n",
            "|===============================+======================+======================|\n",
            "|   0  Tesla K80           Off  | 00000000:00:04.0 Off |                    0 |\n",
            "| N/A   42C    P0    60W / 149W |   7455MiB / 11441MiB |      0%      Default |\n",
            "|                               |                      |                  N/A |\n",
            "+-------------------------------+----------------------+----------------------+\n",
            "                                                                               \n",
            "+-----------------------------------------------------------------------------+\n",
            "| Processes:                                                                  |\n",
            "|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |\n",
            "|        ID   ID                                                   Usage      |\n",
            "|=============================================================================|\n",
            "|  No running processes found                                                 |\n",
            "+-----------------------------------------------------------------------------+\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cH_sB20gzO5Q",
        "cellView": "form"
      },
      "source": [
        "#@title Install dependencies\n",
        "\n",
        "%%capture\n",
        "!pip install transformers\n",
        "!pip install datasets\n",
        "!pip install huggingface-hub==0.7\n",
        "!pip install torch\n",
        "!pip install wandb\n",
        "!pip install lyricsgenius\n",
        "!pip install aiohttp\n",
        "!pip install langdetect\n",
        "!pip install accelerate\n",
        "!pip install --upgrade jax jaxlib \n",
        "!pip install --upgrade git+https://github.com/google/flax.git\n",
        "!pip install tqdm --upgrade\n",
        "!pip install hf-lfs\n",
        "!git config --global user.email \"ale-kor02@mail.ru\"\n",
        "!git config --global user.name \"Aleksey Korshuk\"\n",
        "!git lfs install\n",
        "\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mKHqeuL96mrw"
      },
      "source": [
        "## Pre-process data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BXCZM6vfRHKo",
        "cellView": "form"
      },
      "source": [
        "#@title Attach needed code\n",
        "# %%capture\n",
        "\n",
        "import logging, sys\n",
        "logging.disable(sys.maxsize)\n",
        "\n",
        "from huggingface_hub.hf_api import HfApi\n",
        "hfapi = HfApi()\n",
        "user, namespace = 'huggingartists-app', 'huggingartists'\n",
        "token = hfapi.login(user, namespace)\n",
        "assert hfapi.whoami(token)['name'] == user, \"Could not log into Hugging Face\"\n",
        "!mkdir /root/.huggingface -p\n",
        "text_file = open(\"/root/.huggingface/token\", \"w+\")\n",
        "text_file.write(token)\n",
        "text_file.close() \n",
        "\n",
        "TOKEN = \"q_JK_BFy9OMiG7fGTzL-nUto9JDv3iXI24aYRrQnkOvjSCSbY4BuFIindweRsr5I\"\n",
        "DATASET_LOAD_SCRIPT_URL = \"https://raw.githubusercontent.com/AlekseyKorshuk/huggingartists/main/datasets/dataset.py\"\n",
        "DATASET_CARD_URL = \"https://raw.githubusercontent.com/AlekseyKorshuk/huggingartists/main/datasets/README.md\"\n",
        "MODEL_CARD_URL = \"https://raw.githubusercontent.com/AlekseyKorshuk/huggingartists/main/models/README.md\"\n",
        "\n",
        "from IPython.display import display, HTML, Javascript, clear_output\n",
        "import lyricsgenius\n",
        "from tqdm.notebook import tqdm as bar\n",
        "import requests\n",
        "from bs4 import BeautifulSoup\n",
        "import re\n",
        "from datasets import Dataset, DatasetDict\n",
        "import numpy as np\n",
        "import time\n",
        "import os\n",
        "import json\n",
        "import langdetect\n",
        "import datetime\n",
        "from pathlib import Path\n",
        "import wandb\n",
        "import pathlib\n",
        "import nest_asyncio\n",
        "nest_asyncio.apply()\n",
        "\n",
        "import asyncio\n",
        "from concurrent.futures import ProcessPoolExecutor\n",
        "import sys\n",
        "sys.setrecursionlimit(99999)\n",
        "import aiohttp\n",
        "\n",
        "parser = requests.get(\"https://raw.githubusercontent.com/AlekseyKorshuk/huggingartists/main/datasets/parse.py\").text\n",
        "with open('parse.py', 'w+') as f:\n",
        "  f.write(parser)\n",
        "\n",
        "genius = lyricsgenius.Genius(TOKEN)\n",
        "artist = genius.search_artist(artist_name, max_songs=0, get_full_info=False)\n",
        "\n",
        "\n",
        "from IPython.display import clear_output \n",
        "clear_output()\n",
        "from IPython.utils import io\n",
        "\n",
        "\n",
        "from IPython.display import display, HTML, Javascript, clear_output\n",
        "\n",
        "\n",
        "def stylize():\n",
        "    \"Handle dark mode\"\n",
        "    display(HTML('''\n",
        "    <style>\n",
        "    :root {\n",
        "        --table_bg: #EBF8FF;\n",
        "    }\n",
        "    html[theme=dark] {\n",
        "        --colab-primary-text-color: #d5d5d5;\n",
        "        --table_bg: #2A4365;\n",
        "    }\n",
        "    .jupyter-widgets {\n",
        "        color: var(--colab-primary-text-color);\n",
        "    }\n",
        "    table {\n",
        "        border-collapse: collapse !important;\n",
        "    }\n",
        "    td {\n",
        "        text-align:left !important;\n",
        "        border: solid var(--table_bg) !important;\n",
        "        border-width: 1px 0 !important;\n",
        "        padding: 6px !important;\n",
        "    }\n",
        "    tr:nth-child(even) {\n",
        "        background-color: var(--table_bg) !important;\n",
        "    }\n",
        "    .table_odd {\n",
        "        background-color: var(--table_bg) !important;\n",
        "        margin: 0 !important;\n",
        "    }\n",
        "    .table_even {\n",
        "        border: solid var(--table_bg) !important;\n",
        "        border-width: 1px 0 !important;\n",
        "        margin: 0 !important;\n",
        "    }\n",
        "    .jupyter-widgets {\n",
        "        margin: 6px;\n",
        "    }\n",
        "    .widget-html-content {\n",
        "        font-size: var(--colab-chrome-font-size) !important;\n",
        "        line-height: 1.24 !important;\n",
        "    }\n",
        "    </style>'''))\n",
        "\n",
        "\n",
        "def create_dataset_load_script(model_name):\n",
        "  response = requests.get(DATASET_LOAD_SCRIPT_URL)\n",
        "  text = str(response.text)\n",
        "  text = text.replace(\"MODEL_NAME\", model_name)\n",
        "  with open(f'{model_name}/{model_name}.py', 'w+') as f:\n",
        "    f.write(text)\n",
        "\n",
        "def create_dataset_card(model_name, settings):\n",
        "  response = requests.get(DATASET_CARD_URL)\n",
        "  text = str(response.text)\n",
        "  for key in settings.keys():\n",
        "    text = text.replace(key, str(settings[key]))\n",
        "  with open(f'{model_name}/README.md', 'w+') as f:\n",
        "    f.write(text)\n",
        "\n",
        "def create_model_card(model_name, settings):\n",
        "  response = requests.get(MODEL_CARD_URL)\n",
        "  text = str(response.text)\n",
        "  for key in settings.keys():\n",
        "    text = text.replace(key, str(settings[key]))\n",
        "  with open(f'{model_name}/README.md', 'w+') as f:\n",
        "    f.write(text)\n",
        "\n",
        "def artist_songs(artist_id, per_page=50, page=None, sort='popularity'):\n",
        "  url = f'https://api.genius.com/artists/{artist_id}/songs?sort={sort}&per_page={per_page}&page={page}'\n",
        "  headers = {\n",
        "      'Authorization': f'Bearer {TOKEN}'\n",
        "  }\n",
        "  data = requests.get(\n",
        "      url,\n",
        "      headers=headers, \n",
        "      stream=True\n",
        "  ).json()\n",
        "  return data['response']\n",
        "\n",
        "\n",
        "def get_artist_song_urls(artist_id):\n",
        "  \n",
        "  urls = []\n",
        "  next_page = 1\n",
        "  with bar(total=None) as pbar:\n",
        "    pbar.set_description(\"⏳ Searching songs\")\n",
        "    while next_page is not None:\n",
        "\n",
        "      data = artist_songs(artist.id, per_page=50, page=next_page)\n",
        "      next_page = data['next_page']\n",
        "      \n",
        "      for song in data['songs']:\n",
        "        urls.append(song['url'])\n",
        "      pbar.update(len(data['songs']))   \n",
        "\n",
        "    pbar.set_description(\"✅ Done\")\n",
        "  return urls\n",
        "\n",
        "async def get_song_urls(artist_id):\n",
        "  access_token = 'Bearer ' + TOKEN\n",
        "  authorization_header = {'authorization': access_token}\n",
        "  urls = []\n",
        "  async with aiohttp.ClientSession(headers=authorization_header) as session:\n",
        "    with bar(total=None) as pbar:\n",
        "      pbar.set_description(\"⏳ Searching songs...\")\n",
        "      next_page = 1\n",
        "      while next_page is not None:\n",
        "        async with session.get(f\"https://api.genius.com/artists/{artist_id}/songs?sort=popularity&per_page=50&page={next_page}\", timeout=999) as resp:\n",
        "          response = await resp.json()\n",
        "          response = response['response']\n",
        "        next_page = response['next_page']\n",
        "        \n",
        "        for song in response['songs']:\n",
        "          urls.append(song['url'])\n",
        "        pbar.update(len(response['songs']))\n",
        "      pbar.set_description(\"✅ Done\")\n",
        "  return urls\n",
        "\n",
        "\n",
        "def _get_lyrics(song_url):\n",
        "    text = requests.get(song_url, stream=True).text\n",
        "    \n",
        "    html = BeautifulSoup(text.replace('<br/>', '\\n'), 'html.parser')\n",
        "    div = html.find(\"div\", class_=re.compile(\"^lyrics$|Lyrics__Root\"))\n",
        "    if div is None:\n",
        "      return None\n",
        "\n",
        "    lyrics = div.get_text()\n",
        "\n",
        "    lyrics = re.sub(r'(\\[.*?\\])*', '', lyrics)\n",
        "    lyrics = re.sub('\\n{2}', '\\n', lyrics)  # Gaps between verses\n",
        "    \n",
        "    lyrics = str(lyrics.strip(\"\\n\"))\n",
        "    lyrics = lyrics.replace(\"EmbedShare URLCopyEmbedCopy\", \"\").replace(\"'\", \"\")\n",
        "    lyrics = re.sub(\"[\\(\\[].*?[\\)\\]]\", \"\", lyrics)\n",
        "    lyrics = re.sub(r'\\d+$', '', lyrics)\n",
        "    lyrics = str(lyrics).lstrip().rstrip()\n",
        "    lyrics = str(lyrics).replace(\"\\n\\n\", \"\\n\")\n",
        "    lyrics = str(lyrics).replace(\"\\n\\n\", \"\\n\")\n",
        "    lyrics = re.sub(' +', ' ', lyrics)\n",
        "    lyrics = str(lyrics).replace('\"', \"\")\n",
        "    lyrics = str(lyrics).replace(\"'\", \"\")\n",
        "    lyrics = str(lyrics).replace(\"*\", \"\")\n",
        "    return str(lyrics)\n",
        "\n",
        "\n",
        "def get_lyrics(url):\n",
        "  return _get_lyrics(url)\n",
        "\n",
        "\n",
        "def process_page(html):\n",
        "    '''Meant for CPU-bound workload'''\n",
        "    html = BeautifulSoup(html.replace('<br/>', '\\n'), 'html.parser')\n",
        "    div = html.find(\"div\", class_=re.compile(\"^lyrics$|Lyrics__Root\"))\n",
        "    if div is None:\n",
        "      lyrics = \"\"\n",
        "    else:\n",
        "      lyrics = div.get_text()\n",
        "    \n",
        "    lyrics = re.sub(r'(\\[.*?\\])*', '', lyrics)\n",
        "    lyrics = re.sub('\\n{2}', '\\n', lyrics)  # Gaps between verses\n",
        "    \n",
        "    lyrics = str(lyrics.strip(\"\\n\"))\n",
        "    lyrics = lyrics.replace(\"EmbedShare URLCopyEmbedCopy\", \"\").replace(\"'\", \"\")\n",
        "    lyrics = re.sub(\"[\\(\\[].*?[\\)\\]]\", \"\", lyrics)\n",
        "    lyrics = re.sub(r'\\d+$', '', lyrics)\n",
        "    lyrics = str(lyrics).lstrip().rstrip()\n",
        "    lyrics = str(lyrics).replace(\"\\n\\n\", \"\\n\")\n",
        "    lyrics = str(lyrics).replace(\"\\n\\n\", \"\\n\")\n",
        "    lyrics = re.sub(' +', ' ', lyrics)\n",
        "\n",
        "    lyrics = str(lyrics).replace('\"', \"\")\n",
        "    # lyrics = str(lyrics).replace(\"'\", \"\")\n",
        "    lyrics = str(lyrics).replace(\"*\", \"\")\n",
        "    return lyrics #, re.compile(\"^lyrics$|Lyrics__Root\")\n",
        "\n",
        "\n",
        "async def fetch_page(url, session):\n",
        "    '''Meant for IO-bound workload'''\n",
        "    async with session.get(url, timeout=999) as res:\n",
        "      return await res.text()\n",
        "\n",
        "\n",
        "async def process(url, session, pool, pbar):\n",
        "    html = await fetch_page(url, session)\n",
        "    pbar.update(1)\n",
        "    return await asyncio.wrap_future(pool.submit(process_page, html))\n",
        "\n",
        "\n",
        "async def dispatch(urls, pbar):\n",
        "    print('\\n')\n",
        "    pool = ProcessPoolExecutor()\n",
        "    async with aiohttp.ClientSession() as session:\n",
        "        coros = (process(url, session, pool, pbar) for url in urls)\n",
        "        lyrics = await asyncio.gather(*coros)\n",
        "    return lyrics\n",
        "\n",
        "def create_dataset(lyrics):\n",
        "  train_percentage = 0.9\n",
        "  validation_percentage = 0.07\n",
        "  test_percentage = 0.03\n",
        "\n",
        "  dataset = {}\n",
        "\n",
        "  dataset['train'] = Dataset.from_dict({'text': list(lyrics)})\n",
        "\n",
        "  # train, validation, test = np.split(lyrics, [int(len(lyrics)*train_percentage), int(len(lyrics)*(train_percentage + validation_percentage))])\n",
        "  # if len(list(train)) != 0:\n",
        "  #   dataset['train'] = Dataset.from_dict({'text': list(train)})\n",
        "  # if len(list(validation)) != 0:\n",
        "  #   dataset['validation'] = Dataset.from_dict({'text': list(validation)})\n",
        "  # if len(list(test)) != 0:\n",
        "  #   dataset['test'] = Dataset.from_dict({'text': list(test)})\n",
        "  # del train\n",
        "  # del validation\n",
        "  # del test\n",
        "\n",
        "  datasets = DatasetDict(dataset)\n",
        "  del dataset\n",
        "  return datasets\n",
        "\n",
        "\n",
        "def commit_files(model_name, message):\n",
        "  %cd $model_name\n",
        "  !git add .\n",
        "  !git commit -m \"{message}\"\n",
        "  !git push\n",
        "  %cd ..\n",
        "\n",
        "def parse_dataset(model_name, namespace, artist_id):\n",
        "  \n",
        "  with io.capture_output() as captured:\n",
        "    url = f\"https://huggingface.co/datasets/{namespace}/{model_name}/tree/main\"\n",
        "    data = requests.get(url).text\n",
        "    if data == \"Not Found\":\n",
        "      !huggingface-cli repo create $model_name --type dataset --organization $namespace -y\n",
        "    !rm -rf $model_name\n",
        "    !git clone https://$user:$token@huggingface.co/datasets/$namespace/$model_name\n",
        "    \n",
        "  save_path = f\"{model_name}/datasets.json\"\n",
        "  !python parse.py \\\n",
        "      --artist_id=$artist_id \\\n",
        "      --token=$TOKEN \\\n",
        "      --save_path=$save_path\n",
        "  \n",
        "  with io.capture_output() as captured:\n",
        "    %cd $model_name\n",
        "    # !git lfs untrack \"*.json\"\n",
        "    !git lfs track \"*.json\"\n",
        "    # !rm -rf\n",
        "    %cd ..\n",
        "    # !rm -rf $model_name\n",
        "    # !mkdir $model_name\n",
        "    create_dataset_load_script(model_name)\n",
        "    global artist_url\n",
        "    root_directory = Path(model_name)\n",
        "    size = sum(f.stat().st_size for f in root_directory.glob('**/*') if f.is_file()) / 1000000\n",
        "    \n",
        "    with open(save_path) as f:\n",
        "      data = json.load(f)\n",
        "    \n",
        "    settings = {\n",
        "        'LANGUAGE': 'en',\n",
        "        'USER_HANDLE': model_name,\n",
        "        'YEAR': datetime.datetime.now().year,\n",
        "        'USER_NAME': artist.name,\n",
        "        'USER_PROFILE': artist.image_url,\n",
        "        'TRAIN_SIZE': len(data['train']),\n",
        "        'SIZE': str(size)\n",
        "    }\n",
        "    create_dataset_card(model_name, settings)\n",
        "    commit_files(model_name, namespace)\n",
        "    !rm -rf $model_name\n",
        "\n",
        "from datasets import ClassLabel\n",
        "import random\n",
        "import pandas as pd\n",
        "from IPython.display import display, HTML\n",
        "\n",
        "\n",
        "def show_random_elements(dataset, num_examples=3):\n",
        "    assert num_examples <= len(dataset), \"Can't pick more elements than there are in the dataset.\"\n",
        "    picks = []\n",
        "    for _ in range(num_examples):\n",
        "        pick = random.randint(0, len(dataset)-1)\n",
        "        while pick in picks:\n",
        "            pick = random.randint(0, len(dataset)-1)\n",
        "        picks.append(pick)\n",
        "    print(dataset[picks]['text'])\n",
        "    print(len(dataset[picks]['text']))\n",
        "    df = pd.DataFrame(dataset[picks]['text'])\n",
        "    for column, typ in dataset.features.items():\n",
        "        if isinstance(typ, ClassLabel):\n",
        "            df[column] = df[column].transform(lambda i: typ.names[i])\n",
        "    display(HTML(df.to_html()))\n",
        "\n",
        "\n",
        "def tokenize_function(examples):\n",
        "    return tokenizer(examples[\"text\"])\n",
        "\n",
        "\n",
        "def group_texts(examples):\n",
        "    # Concatenate all texts.\n",
        "    concatenated_examples = {k: sum(examples[k], []) for k in examples.keys()}\n",
        "    total_length = len(concatenated_examples[list(examples.keys())[0]])\n",
        "    # We drop the small remainder, we could add padding if the model supported it instead of this drop, you can\n",
        "        # customize this part to your needs.\n",
        "    total_length = (total_length // block_size) * block_size\n",
        "    # Split by chunks of max_len.\n",
        "    result = {\n",
        "        k: [t[i : i + block_size] for i in range(0, total_length, block_size)]\n",
        "        for k, t in concatenated_examples.items()\n",
        "    }\n",
        "    result[\"labels\"] = result[\"input_ids\"].copy()\n",
        "    return result\n",
        "\n",
        "\n",
        "def show_result(dataset, num_examples=3):\n",
        "    assert num_examples <= len(dataset), \"Can't pick more elements than there are in the dataset.\"\n",
        "    picks = []\n",
        "    data = []\n",
        "    for _ in range(num_examples):\n",
        "        pick = random.randint(0, len(dataset)-1)\n",
        "        while pick in picks:\n",
        "            pick = random.randint(0, len(dataset)-1)\n",
        "        picks.append(pick)\n",
        "        data.append(str(dataset[pick]))  \n",
        "    df = pd.DataFrame(data)\n",
        "    # for column, typ in dataset.features.items():\n",
        "    #     if isinstance(typ, ClassLabel):\n",
        "    #         df[column] = df[column].transform(lambda i: typ.names[i])\n",
        "    display(HTML(df.to_html(index=False).replace(\"\\\\n\",\"<br>\")))\n",
        "\n",
        "\n",
        "def post_process(output_sequences):\n",
        "    predictions = []\n",
        "    generated_sequences = []\n",
        "\n",
        "    max_repeat = 2\n",
        "\n",
        "    # decode prediction\n",
        "    for generated_sequence_idx, generated_sequence in enumerate(output_sequences):\n",
        "        generated_sequence = generated_sequence.tolist()\n",
        "        text = tokenizer.decode(generated_sequence, clean_up_tokenization_spaces=True, skip_special_tokens=True)\n",
        "        generated_sequences.append(text.strip())\n",
        "                    \n",
        "    for i, g in enumerate(generated_sequences):\n",
        "        res = str(g).replace('\\n\\n\\n', '\\n').replace('\\n\\n', '\\n')\n",
        "        lines = res.split('\\n')\n",
        "        # print(lines)\n",
        "        i = max_repeat\n",
        "        while i != len(lines):\n",
        "          remove_count = 0\n",
        "          for index in range(0, max_repeat):\n",
        "            # print(i - index - 1, i - index)\n",
        "            if lines[i - index - 1] == lines[i - index]:\n",
        "              remove_count += 1\n",
        "          if remove_count == max_repeat:\n",
        "            lines.pop(i)\n",
        "            i -= 1\n",
        "          else:\n",
        "            i += 1\n",
        "        predictions.append('\\n'.join(lines))\n",
        "\n",
        "    return predictions\n",
        "\n",
        "def get_table(table_data):\n",
        "  html = (\"</head>\\r\\n\"\n",
        "    \"<body>\\r\\n\\r\\n\"\n",
        "    \"<h2></h2>\"\n",
        "    \"\\r\\n\\r\\n\"\n",
        "    \"<table>\\r\\n\"\n",
        "    \"    <colgroup>\\r\\n\"\n",
        "    \"       <col span=\\\"1\"\n",
        "    \"\\\" style=\\\"width: 10\"\n",
        "    \"%;\\\">\\r\\n\"\n",
        "    \"       <col span=\\\"1\"\n",
        "    \"\\\" style=\\\"width: 10\"\n",
        "    \"0%;\\\">\\r\\n\"\n",
        "    \"    </colgroup>\\r\\n\"\n",
        "    f\"{' '.join(table_data)}\"\n",
        "    \"</table>\\r\\n\\r\\n\"\n",
        "    \"</body>\\r\\n\"\n",
        "    \"</html>\")\n",
        "  \n",
        "  return html\n",
        "\n",
        "def get_share_button(url):\n",
        "    return f'''\n",
        "            <div style=\"width: 76px;\">\n",
        "                <a target=\"_blank\" href=\"{url}\" style='background-color:rgb(27, 149, 224);border-bottom-left-radius:4px;border-bottom-right-radius:4px;border-top-left-radius:4px;border-top-right-radius:4px;box-sizing:border-box;color:rgb(255, 255, 255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\", Arial, sans-serif;font-size:13px;font-stretch:100%;font-style:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;height:28px;line-height:26px;outline-color:rgb(255, 255, 255);outline-style:none;outline-width:0px;padding-bottom:1px;padding-left:9px;padding-right:10px;padding-top:1px;position:relative;text-align:left;text-decoration-color:rgb(255, 255, 255);text-decoration-line:none;text-decoration-style:solid;text-decoration-thickness:auto;user-select:none;vertical-align:top;white-space:nowrap;zoom:1;'>\n",
        "                <i style='background-attachment:scroll;background-clip:border-box;background-color:rgba(0,0,0,0);background-image:url(data:image/svg+xml,%3Csvg%20xmlns%3D%22http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%22%20viewBox%3D%220%200%2072%2072%22%3E%3Cpath%20fill%3D%22none%22%20d%3D%22M0%200h72v72H0z%22%2F%3E%3Cpath%20class%3D%22icon%22%20fill%3D%22%23fff%22%20d%3D%22M68.812%2015.14c-2.348%201.04-4.87%201.744-7.52%202.06%202.704-1.62%204.78-4.186%205.757-7.243-2.53%201.5-5.33%202.592-8.314%203.176C56.35%2010.59%2052.948%209%2049.182%209c-7.23%200-13.092%205.86-13.092%2013.093%200%201.026.118%202.02.338%202.98C25.543%2024.527%2015.9%2019.318%209.44%2011.396c-1.125%201.936-1.77%204.184-1.77%206.58%200%204.543%202.312%208.552%205.824%2010.9-2.146-.07-4.165-.658-5.93-1.64-.002.056-.002.11-.002.163%200%206.345%204.513%2011.638%2010.504%2012.84-1.1.298-2.256.457-3.45.457-.845%200-1.666-.078-2.464-.23%201.667%205.2%206.5%208.985%2012.23%209.09-4.482%203.51-10.13%205.605-16.26%205.605-1.055%200-2.096-.06-3.122-.184%205.794%203.717%2012.676%205.882%2020.067%205.882%2024.083%200%2037.25-19.95%2037.25-37.25%200-.565-.013-1.133-.038-1.693%202.558-1.847%204.778-4.15%206.532-6.774z%22%2F%3E%3C%2Fsvg%3E);background-origin:padding-box;background-position-x:0px;background-position-y:0px;background-repeat-x;background-repeat-y;background-size:auto;color:rgb(255,255,255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\",Arial,sans-serif;font-size:13px;font-stretch:100%;font-style:italic;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;height:18px;line-height:26px;position:relative;text-align:left;text-decoration-thickness:auto;top:4px;user-select:none;white-space:nowrap;width:18px;'></i>\n",
        "                <span style='color:rgb(255,255,255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\",Arial,sans-serif;font-size:13px;font-stretch:100%;font-style:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;line-height:26px;margin-left:4px;text-align:left;text-decoration-thickness:auto;user-select:none;vertical-align:top;white-space:nowrap;zoom:1;'>Tweet</span>\n",
        "            </a>\n",
        "            </div>\n",
        "            '''\n",
        "\n",
        "def share_model_table(artist_name, model_name):\n",
        "  url = f\"https://twitter.com/intent/tweet?text=I created an AI bot of {artist_name} with %23huggingartists!%0APlay with my model or create your own! &url=https://huggingface.co/huggingartists/{model_name}\"\n",
        "\n",
        "  share_button = get_share_button(url)\n",
        "  table_data = [\n",
        "        f'<tr><td>{share_button}</td><td>🎉 Share {artist_name} model: <a href=\"https://huggingface.co/huggingartists/{model_name}\">https://huggingface.co/huggingartists/{model_name}</a></td></tr>'    \n",
        "  ]\n",
        "  return get_table(table_data)\n",
        "\n",
        "def get_share_lyrics_url(artist_name, model_name, lyrics):\n",
        "   return \"https://twitter.com/intent/tweet?text=I created an AI bot of \" + artist_name + \" with %23huggingartists!%0A%0ABrand new song:%0A\" + lyrics.replace('\\n', '%0A').replace('\"', '%22') + \"%0A%0APlay with my model or create your own! &url=https://huggingface.co/huggingartists/\" + model_name"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pzpqELj0Q5l2",
        "cellView": "form"
      },
      "source": [
        "#@title Collect data\n",
        "if artist is not None:\n",
        "  time.sleep(0.1)\n",
        "  artist_dict = genius.artist(artist.id)['artist']\n",
        "  artist_url = str(artist_dict['url'])\n",
        "  model_name = artist_url[artist_url.rfind('/') + 1:].lower()\n",
        "\n",
        "  datasets = None\n",
        "  if check_dataset:\n",
        "    print(\"Check existing dataset first...\")\n",
        "    url = f\"https://huggingface.co/datasets/{namespace}/{model_name}/tree/main\"\n",
        "    data = requests.get(url).text\n",
        "    if data != \"Not Found\":\n",
        "      from datasets import load_dataset\n",
        "      datasets = load_dataset(f\"{namespace}/{model_name}\")\n",
        "      print(\"Dataset downloaded!\")\n",
        "  \n",
        "  if datasets == None:\n",
        "    if check_dataset:\n",
        "      print(\"Dataset does not exist!\")\n",
        "    parse_dataset(model_name, namespace, int(artist.id))\n",
        "    from datasets import load_dataset\n",
        "    datasets = load_dataset(f\"{namespace}/{model_name}\")\n",
        "  # show_random_elements(datasets[\"train\"], num_examples=3)\n",
        "  train_percentage = 0.85\n",
        "  validation_percentage = 0.15\n",
        "  test_percentage = 0\n",
        "  array = datasets['train']['text']\n",
        "  random.shuffle(array)\n",
        "  train, validation, test = np.split(array, [int(len(datasets['train']['text'])*train_percentage), int(len(datasets['train']['text'])*(train_percentage + validation_percentage))])\n",
        "\n",
        "  datasets = DatasetDict(\n",
        "      {\n",
        "          'train': Dataset.from_dict({'text': list(train)}),\n",
        "          'validation': Dataset.from_dict({'text': list(validation)}),\n",
        "          'test': Dataset.from_dict({'text': list(test)})\n",
        "      }\n",
        "  )\n",
        "else:\n",
        "  import Exception\n",
        "  raise Exception(\"Artist does not exist!\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IuVmcryUuBKT"
      },
      "source": [
        "## Clone or create repository "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "k7LL37IJt-_k",
        "cellView": "form"
      },
      "source": [
        "#@title Clone or create repository\n",
        "with io.capture_output() as captured:\n",
        "  !rm -rf $model_name\n",
        "  repo_url = hfapi.create_repo(token=token, name=model_name, organization=namespace, exist_ok=True)\n",
        "  !git clone https://$user:$token@huggingface.co/$namespace/$model_name"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "L8kjz49JEa-5"
      },
      "source": [
        "## Map datasets and set up the Trainer"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iAYlS40Z3l-v",
        "cellView": "form"
      },
      "source": [
        "#@title Download model and tokenizer\n",
        "from transformers import AutoTokenizer, AutoModelForCausalLM, Trainer, TrainingArguments\n",
        "\n",
        "try:\n",
        "  tokenizer = AutoTokenizer.from_pretrained(f\"{namespace}/{model_name}\")\n",
        "  model = AutoModelForCausalLM.from_pretrained(f\"{namespace}/{model_name}\", cache_dir=pathlib.Path('cache').resolve())\n",
        "except:\n",
        "  tokenizer = AutoTokenizer.from_pretrained(\"gpt2\")\n",
        "  model = AutoModelForCausalLM.from_pretrained(\"gpt2\", cache_dir=pathlib.Path('cache').resolve())\n",
        "\n",
        "# tokenizer.add_special_tokens({'pad_token': '[PAD]'})\n",
        "# model.resize_token_embeddings(len(tokenizer))\n",
        "\n",
        "tokenized_datasets = datasets.map(tokenize_function, batched=True, num_proc=1, remove_columns=[\"text\"])\n",
        "\n",
        "# block_size = tokenizer.model_max_length\n",
        "block_size = int(tokenizer.model_max_length / 4)\n",
        "\n",
        "lm_datasets = tokenized_datasets.map(\n",
        "    group_texts,\n",
        "    batched=True,\n",
        "    batch_size=1000,\n",
        "    num_proc=1,\n",
        ")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uFFCYtKLZ7G1",
        "cellView": "form"
      },
      "source": [
        "#@title Set up the Trainer\n",
        "\n",
        "trainer_state_path = f'{model_name}/trainer_state.json'\n",
        "if os.path.isfile(trainer_state_path):\n",
        "  f = open (trainer_state_path, \"r\")\n",
        "  trainer_state = json.loads(f.read()) \n",
        "  f.close()\n",
        "  epoch = trainer_state['epoch']\n",
        "  num_train_epochs += epoch\n",
        "\n",
        "seed_data = random.randint(0,2**32-1)\n",
        "# Set-up Trainer\n",
        "os.environ['WANDB_WATCH'] = 'false'  # used in Trainer\n",
        "training_args = TrainingArguments(\n",
        "    f\"output/{model_name}\",\n",
        "    overwrite_output_dir=True,\n",
        "    evaluation_strategy = \"epoch\",\n",
        "    learning_rate=1.372e-4,\n",
        "    weight_decay=0.01,\n",
        "    num_train_epochs=num_train_epochs,\n",
        "    save_total_limit=10,\n",
        "    save_strategy='epoch',\n",
        "    save_steps=1,\n",
        "    report_to=None,\n",
        "    seed=seed_data,\n",
        "    logging_steps=5,\n",
        "    do_eval=True,\n",
        "    eval_steps=1,\n",
        "    load_best_model_at_end=True\n",
        "    # disable_tqdm=True\n",
        "    # load_best_model_at_end=True\n",
        ")\n",
        "\n",
        "trainer = Trainer(\n",
        "    model=model,\n",
        "    # tokenizer=tokenizer,\n",
        "    args=training_args,\n",
        "    train_dataset=lm_datasets[\"train\"],\n",
        "    eval_dataset=lm_datasets[\"validation\"]\n",
        ")\n",
        "\n",
        "from transformers import get_cosine_schedule_with_warmup\n",
        "train_dataloader = trainer.get_train_dataloader()\n",
        "num_train_steps = len(train_dataloader)\n",
        "trainer.create_optimizer_and_scheduler(num_train_steps)\n",
        "trainer.lr_scheduler = get_cosine_schedule_with_warmup(\n",
        "      trainer.optimizer,\n",
        "      num_warmup_steps=0,\n",
        "      num_training_steps=num_train_steps\n",
        ")\n",
        "\n",
        "trainer.model.config.task_specific_params['text-generation'] = {\n",
        "                    'do_sample': True,\n",
        "                    'min_length': 100,\n",
        "                    'max_length': 200,\n",
        "                    'temperature': 1.,\n",
        "                    'top_p': 0.95,\n",
        "                    # 'prefix': '<|endoftext|>',\n",
        "                    }"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fGaG3_A5EuTV"
      },
      "source": [
        "## Train and upload the model"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZCvDGhVH7jD1",
        "cellView": "form"
      },
      "source": [
        "#@title W&B Setup\n",
        "\n",
        "from torch import __version__ as torch_version\n",
        "from transformers import __version__ as transformers_version\n",
        "\n",
        "with io.capture_output() as captured:\n",
        "  wandb.login(key='cd33331f97be3145253704fc38efef090ffe8151') # huggingartists service key\n",
        "\n",
        "WANDB_PROJECT = 'huggingartists'\n",
        "WANDB_NOTES = \"Github repo: https://github.com/AlekseyKorshuk/huggingartists\"\n",
        "WANDB_ENTITY = 'huggingartists'\n",
        "VERSION = 1.0\n",
        "os.environ['WANDB_NOTEBOOK_NAME'] = 'huggingartists-demo.ipynb'  # used in wandb cli\n",
        "model_card_settings = {}\n",
        "\n",
        "def setup_wandb():\n",
        "  global model_card_settings\n",
        "  run = wandb.init(name=f\"{model_name}-preprocess\",\n",
        "          job_type='preprocess',\n",
        "          config={'huggingartists version':VERSION,\n",
        "              'handle':model_name,\n",
        "              'seed data':seed_data},\n",
        "          project = WANDB_PROJECT,\n",
        "          entity = WANDB_ENTITY,\n",
        "          notes = WANDB_NOTES,\n",
        "          reinit=True)\n",
        "    \n",
        "  # log raw tweets as input\n",
        "  global metadata\n",
        "  metadata={'handle':model_name,\n",
        "        'huggingartists version': VERSION}\n",
        "  artifact_input = wandb.Artifact(\n",
        "      f\"lyrics-{model_name}\",\n",
        "      type='raw-dataset',\n",
        "      description=f\"Lyrics from {model_name} downloaded with Genius\",                            \n",
        "      metadata=metadata)\n",
        "  with artifact_input.new_file('lyrics.txt') as f:\n",
        "    json.dump(datasets['train'].to_dict(), f, indent=0, ensure_ascii=False)\n",
        "  run.use_artifact(artifact_input)\n",
        "  # log dataset as output                        \n",
        "  metadata={'handle':model_name,\n",
        "        'seed data': seed_data,\n",
        "        'epochs': num_train_epochs,\n",
        "        'huggingartists version': VERSION}\n",
        "  global artifact_dataset\n",
        "  artifact_dataset = wandb.Artifact(\n",
        "    f\"dataset-{model_name}\",\n",
        "    type='train-dataset',\n",
        "    description=f\"Dataset created from lyrics of {model_name}\",\n",
        "    metadata=metadata)\n",
        "  with open(f\"data_{model_name}_train.txt\", 'w', encoding='utf-8') as f:\n",
        "    f.write('\\n\\n\\n'.join(datasets['train']['text']))\n",
        "  artifact_dataset.add_file(f\"data_{model_name}_train.txt\")\n",
        "  run.log_artifact(artifact_dataset)\n",
        "\n",
        "  # keep track of url\n",
        "  wandb_url = wandb.run.get_url()\n",
        "  model_card_settings['WANDB_PREPROCESS'] = str(wandb_url)\n",
        "\n",
        "  combined_dict = {**model.config.to_dict(), **training_args.to_sanitized_dict()}\n",
        "  run = wandb.init(name=f\"{model_name}-train\",\n",
        "          job_type='train',\n",
        "          config={'huggingartists version':VERSION,\n",
        "              'pytorch version': torch_version,\n",
        "              'transformers version': transformers_version,\n",
        "              'handle':model_name,\n",
        "              **combined_dict},\n",
        "          project = WANDB_PROJECT,\n",
        "          entity = WANDB_ENTITY,\n",
        "          notes = WANDB_NOTES,\n",
        "          reinit=True)\n",
        "\n",
        "\n",
        "  # keep track of url\n",
        "  wandb_url = wandb.run.get_url()\n",
        "  model_card_settings['WANDB_TRAIN'] = wandb_url\n",
        "\n",
        "\n",
        "\n",
        "  # log dataset and pretrained model\n",
        "  artifact_dataset.wait()\n",
        "  run.use_artifact(artifact_dataset)\n",
        "  artifact_gpt2 = wandb.Artifact(\n",
        "    f'gpt2',\n",
        "    type='pretrained-model',\n",
        "    description=f'Pretrained model from OpenAI downloaded from 🤗 Transformers: https://huggingface.co/gpt2',\n",
        "    metadata={'huggingartists version': VERSION})\n",
        "  artifact_gpt2.add_dir('cache', name='gpt2')\n",
        "  run.use_artifact(artifact_gpt2)\n",
        "  return run\n",
        "\n",
        "with io.capture_output() as captured:\n",
        "  run = setup_wandb()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 921
        },
        "id": "Ci8RqgFt71qS",
        "cellView": "form",
        "outputId": "d19908ef-4f2c-4315-badb-c05801a56be3"
      },
      "source": [
        "#@title W&B Visualization\n",
        "from IPython.display import HTML\n",
        "\n",
        "url = wandb.run._get_run_url() + \"?jupyter=true\"\n",
        "\n",
        "html = HTML(\n",
        "    \"\"\"<iframe src=\"%s\" style=\"border:none;width:100%%;height:900px\">\n",
        "                </iframe>\"\"\"\n",
        "                % url\n",
        "    )\n",
        "\n",
        "display(\n",
        "    html\n",
        ")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<iframe src=\"https://wandb.ai/huggingartists/huggingartists/runs/3p5781qk?jupyter=true\" style=\"border:none;width:100%;height:900px\">\n",
              "                </iframe>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sLw57xhO_9uV",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
          "referenced_widgets": [
            "ee2403a1576140d59842c00069bcee09",
            "c6396f0506b44f778f465d86083171fa",
            "96f6b1e453db4c5bb18fcf61427b2ed5",
            "959a8cb183f044c0a43f5c68f209db82",
            "f02d6bc8f47c4bebb57e1420d8e372cb",
            "d000f050ed664dea9d2756ee31dc2d13",
            "c6310a4aaa3948d085682d59fc01a5d3",
            "1a6ccec3d2a248bfb5046cb978b8f3ca",
            "b1a0bd8051004949b23f2a71f97eb31f",
            "12fa8b07fc624c1f85a90d9e3603a57c",
            "50c0b87c60124fc9b2cdeb00fba72cd7"
          ]
        },
        "cellView": "form",
        "outputId": "d4f9be9c-20de-463d-f5bf-33081057e5df"
      },
      "source": [
        "#@title Train the model\n",
        "\n",
        "# from IPython.display import HTML\n",
        "\n",
        "# display(\n",
        "#     html\n",
        "# )\n",
        "\n",
        "import torch\n",
        "torch.cuda.empty_cache()\n",
        "if os.path.isfile(trainer_state_path):\n",
        "  try:\n",
        "    data = trainer.train(resume_from_checkpoint=model_name)\n",
        "  except:\n",
        "    data = trainer.train()\n",
        "else:\n",
        "  data = trainer.train()\n",
        "# print(data)\n",
        "\n",
        "try:\n",
        "  with open('data.txt') as json_file:\n",
        "      evaluation = json.load(json_file)\n",
        "  eval_loss = evaluation['eval_loss']\n",
        "except:\n",
        "  eval_loss = 9999999\n",
        "  \n",
        "evaluation = trainer.evaluate()\n",
        "if evaluation['eval_loss'] < eval_loss:\n",
        "  save_model = True\n",
        "  with open(f'{model_name}/evaluation.txt', 'w') as outfile:\n",
        "    json.dump(evaluation, outfile)\n",
        "else:\n",
        "  save_model = False"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "ee2403a1576140d59842c00069bcee09",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "0it [00:00, ?it/s]"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "    <div>\n",
              "      \n",
              "      <progress value='2014' max='2014' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
              "      [2014/2014 1:02:22, Epoch 106/106]\n",
              "    </div>\n",
              "    <table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: left;\">\n",
              "      <th>Epoch</th>\n",
              "      <th>Training Loss</th>\n",
              "      <th>Validation Loss</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <td>7</td>\n",
              "      <td>2.099800</td>\n",
              "      <td>2.614194</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>8</td>\n",
              "      <td>1.947000</td>\n",
              "      <td>2.629248</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>9</td>\n",
              "      <td>1.629800</td>\n",
              "      <td>2.651782</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>10</td>\n",
              "      <td>1.434400</td>\n",
              "      <td>2.691366</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>11</td>\n",
              "      <td>1.475400</td>\n",
              "      <td>2.746285</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>12</td>\n",
              "      <td>1.418400</td>\n",
              "      <td>2.824387</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>13</td>\n",
              "      <td>1.015100</td>\n",
              "      <td>2.876097</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>14</td>\n",
              "      <td>1.052400</td>\n",
              "      <td>2.852467</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>15</td>\n",
              "      <td>0.888100</td>\n",
              "      <td>3.030415</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>16</td>\n",
              "      <td>0.996600</td>\n",
              "      <td>3.236509</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>17</td>\n",
              "      <td>0.699400</td>\n",
              "      <td>3.251048</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>18</td>\n",
              "      <td>0.758600</td>\n",
              "      <td>3.395446</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>19</td>\n",
              "      <td>0.604900</td>\n",
              "      <td>3.475355</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>20</td>\n",
              "      <td>0.433600</td>\n",
              "      <td>3.573740</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>21</td>\n",
              "      <td>0.444000</td>\n",
              "      <td>3.685168</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>22</td>\n",
              "      <td>0.370100</td>\n",
              "      <td>3.830919</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>23</td>\n",
              "      <td>0.357900</td>\n",
              "      <td>3.795492</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>24</td>\n",
              "      <td>0.324300</td>\n",
              "      <td>3.846162</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>25</td>\n",
              "      <td>0.283100</td>\n",
              "      <td>3.911623</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>26</td>\n",
              "      <td>0.235900</td>\n",
              "      <td>4.041982</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>27</td>\n",
              "      <td>0.209500</td>\n",
              "      <td>4.048786</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>28</td>\n",
              "      <td>0.182000</td>\n",
              "      <td>4.104511</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>29</td>\n",
              "      <td>0.199800</td>\n",
              "      <td>4.149124</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>30</td>\n",
              "      <td>0.151200</td>\n",
              "      <td>4.207634</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>31</td>\n",
              "      <td>0.169700</td>\n",
              "      <td>4.241185</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>32</td>\n",
              "      <td>0.114900</td>\n",
              "      <td>4.305730</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>33</td>\n",
              "      <td>0.130100</td>\n",
              "      <td>4.300008</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>34</td>\n",
              "      <td>0.122600</td>\n",
              "      <td>4.368078</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>35</td>\n",
              "      <td>0.152400</td>\n",
              "      <td>4.393700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>36</td>\n",
              "      <td>0.077000</td>\n",
              "      <td>4.478081</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>37</td>\n",
              "      <td>0.103900</td>\n",
              "      <td>4.437718</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>38</td>\n",
              "      <td>0.076000</td>\n",
              "      <td>4.479358</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>39</td>\n",
              "      <td>0.092800</td>\n",
              "      <td>4.442643</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>40</td>\n",
              "      <td>0.084900</td>\n",
              "      <td>4.598237</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>41</td>\n",
              "      <td>0.078500</td>\n",
              "      <td>4.487538</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>42</td>\n",
              "      <td>0.060900</td>\n",
              "      <td>4.596984</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>43</td>\n",
              "      <td>0.092900</td>\n",
              "      <td>4.538696</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>44</td>\n",
              "      <td>0.053000</td>\n",
              "      <td>4.600017</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>45</td>\n",
              "      <td>0.070300</td>\n",
              "      <td>4.585979</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>46</td>\n",
              "      <td>0.053900</td>\n",
              "      <td>4.652865</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>47</td>\n",
              "      <td>0.059400</td>\n",
              "      <td>4.633067</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>48</td>\n",
              "      <td>0.051800</td>\n",
              "      <td>4.666164</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>49</td>\n",
              "      <td>0.058400</td>\n",
              "      <td>4.656873</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>50</td>\n",
              "      <td>0.047700</td>\n",
              "      <td>4.647537</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>51</td>\n",
              "      <td>0.047000</td>\n",
              "      <td>4.678836</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>52</td>\n",
              "      <td>0.038700</td>\n",
              "      <td>4.656852</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>53</td>\n",
              "      <td>0.047100</td>\n",
              "      <td>4.720753</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>54</td>\n",
              "      <td>0.045800</td>\n",
              "      <td>4.722589</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>55</td>\n",
              "      <td>0.048100</td>\n",
              "      <td>4.737137</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>56</td>\n",
              "      <td>0.035900</td>\n",
              "      <td>4.757367</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>57</td>\n",
              "      <td>0.044000</td>\n",
              "      <td>4.779588</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>58</td>\n",
              "      <td>0.031500</td>\n",
              "      <td>4.749435</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>59</td>\n",
              "      <td>0.030300</td>\n",
              "      <td>4.773011</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>60</td>\n",
              "      <td>0.037600</td>\n",
              "      <td>4.750817</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>61</td>\n",
              "      <td>0.037300</td>\n",
              "      <td>4.786413</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>62</td>\n",
              "      <td>0.028100</td>\n",
              "      <td>4.770158</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>63</td>\n",
              "      <td>0.043000</td>\n",
              "      <td>4.815156</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>64</td>\n",
              "      <td>0.027800</td>\n",
              "      <td>4.819550</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>65</td>\n",
              "      <td>0.042500</td>\n",
              "      <td>4.839301</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>66</td>\n",
              "      <td>0.028300</td>\n",
              "      <td>4.845079</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>67</td>\n",
              "      <td>0.034200</td>\n",
              "      <td>4.810131</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>68</td>\n",
              "      <td>0.029700</td>\n",
              "      <td>4.941418</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>69</td>\n",
              "      <td>0.030200</td>\n",
              "      <td>4.864980</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>70</td>\n",
              "      <td>0.021800</td>\n",
              "      <td>4.945081</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>71</td>\n",
              "      <td>0.033500</td>\n",
              "      <td>4.955899</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>72</td>\n",
              "      <td>0.027200</td>\n",
              "      <td>4.912611</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>73</td>\n",
              "      <td>0.021000</td>\n",
              "      <td>4.899780</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>74</td>\n",
              "      <td>0.023500</td>\n",
              "      <td>4.899014</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>75</td>\n",
              "      <td>0.030200</td>\n",
              "      <td>4.928937</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>76</td>\n",
              "      <td>0.020300</td>\n",
              "      <td>4.892313</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>77</td>\n",
              "      <td>0.023400</td>\n",
              "      <td>4.920340</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>78</td>\n",
              "      <td>0.021100</td>\n",
              "      <td>4.939473</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>79</td>\n",
              "      <td>0.027000</td>\n",
              "      <td>4.937385</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>80</td>\n",
              "      <td>0.026200</td>\n",
              "      <td>4.937868</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>81</td>\n",
              "      <td>0.027600</td>\n",
              "      <td>4.936015</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>82</td>\n",
              "      <td>0.019900</td>\n",
              "      <td>4.946178</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>83</td>\n",
              "      <td>0.029300</td>\n",
              "      <td>4.949464</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>84</td>\n",
              "      <td>0.022100</td>\n",
              "      <td>4.996701</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>85</td>\n",
              "      <td>0.019100</td>\n",
              "      <td>4.951455</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>86</td>\n",
              "      <td>0.021600</td>\n",
              "      <td>5.052703</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>87</td>\n",
              "      <td>0.023300</td>\n",
              "      <td>5.021987</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>88</td>\n",
              "      <td>0.018600</td>\n",
              "      <td>5.005445</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>89</td>\n",
              "      <td>0.026700</td>\n",
              "      <td>5.023168</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>90</td>\n",
              "      <td>0.026300</td>\n",
              "      <td>5.042933</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>91</td>\n",
              "      <td>0.024300</td>\n",
              "      <td>5.033708</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>92</td>\n",
              "      <td>0.017600</td>\n",
              "      <td>5.028059</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>93</td>\n",
              "      <td>0.022900</td>\n",
              "      <td>5.005255</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>94</td>\n",
              "      <td>0.023300</td>\n",
              "      <td>5.023060</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>95</td>\n",
              "      <td>0.026400</td>\n",
              "      <td>5.012453</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>96</td>\n",
              "      <td>0.016700</td>\n",
              "      <td>5.021945</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>97</td>\n",
              "      <td>0.024200</td>\n",
              "      <td>5.035902</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>98</td>\n",
              "      <td>0.018000</td>\n",
              "      <td>5.077088</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>99</td>\n",
              "      <td>0.024000</td>\n",
              "      <td>5.108748</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>100</td>\n",
              "      <td>0.017500</td>\n",
              "      <td>5.089485</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>101</td>\n",
              "      <td>0.016400</td>\n",
              "      <td>5.090783</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>102</td>\n",
              "      <td>0.013700</td>\n",
              "      <td>5.065732</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>103</td>\n",
              "      <td>0.021900</td>\n",
              "      <td>5.068276</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>104</td>\n",
              "      <td>0.023900</td>\n",
              "      <td>5.124930</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>105</td>\n",
              "      <td>0.023500</td>\n",
              "      <td>5.084531</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>106</td>\n",
              "      <td>0.024200</td>\n",
              "      <td>5.132873</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table><p>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "    <div>\n",
              "      \n",
              "      <progress value='4' max='4' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
              "      [4/4 00:01]\n",
              "    </div>\n",
              "    "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YxvGgAlqNAYc",
        "cellView": "form"
      },
      "source": [
        "#@title Create model card\n",
        "\n",
        "from os import listdir\n",
        "from os.path import isfile, join, isdir\n",
        "# mypath = f'output/{model_name}'\n",
        "# checkpoints = [join(mypath, f) for f in listdir(mypath) if isdir(join(mypath, f)) and 'checkpoint' in join(mypath, f)]\n",
        "# checkpoint = checkpoints[0]\n",
        "checkpoint = trainer.state.best_model_checkpoint\n",
        "tokenizer.save_pretrained(checkpoint)\n",
        "\n",
        "!mv $checkpoint/* $model_name\n",
        "model_card_settings['LANGUAGE'] = 'en'\n",
        "model_card_settings['USER_HANDLE'] = model_name\n",
        "model_card_settings['YEAR'] = datetime.datetime.now().year\n",
        "model_card_settings['USER_NAME'] = artist.name\n",
        "model_card_settings['USER_PROFILE'] = artist.image_url\n",
        "\n",
        "create_model_card(model_name, model_card_settings)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jmUVMeNuFnEa",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "cellView": "form",
        "outputId": "602cade7-9584-4255-ea57-d3fdf624a33b"
      },
      "source": [
        "#@title W&B Artifacts\n",
        "global metadata\n",
        "metadata={'model url':f\"https://huggingface.co/huggingartists/{model_name}\",\n",
        "\t\t  'seed trainer':seed_data,\n",
        "\t\t  **metadata}\n",
        "artifact_trained = wandb.Artifact(\n",
        "\tmodel_name,\n",
        "\ttype='finetuned-model',\n",
        "\tdescription=f\"Model fine-tuned on lyrics from {model_name}\",\n",
        "\tmetadata=metadata)\n",
        "\n",
        "hf_urls = []\n",
        "model_path = pathlib.Path(model_name)\n",
        "hf_urls = [f'https://huggingface.co/huggingtweets/{model_name}/resolve/main/{f.name}' for f in model_path.glob('*') if f.suffix]\n",
        "for hf_url in hf_urls:\n",
        "\tartifact_trained.add_reference(hf_url, checksum = False)\n",
        "global run\n",
        "run.log_artifact(artifact_trained)\n",
        "print(\"\")\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QGw7lBeVTVel",
        "cellView": "form"
      },
      "source": [
        "#@title Upload the model\n",
        "\n",
        "url = f\"https://huggingface.co/{namespace}/{model_name}/raw/main/trainer_state.json\"\n",
        "data = requests.get(url).text\n",
        "try:\n",
        "  data = json.loads(data)\n",
        "except:\n",
        "  data = None\n",
        "if (data is None or data['epoch'] <= num_train_epochs) and save_model:\n",
        "  with io.capture_output() as captured:\n",
        "    # from accelerate import Accelerator\n",
        "    # accelerator = Accelerator()\n",
        "    # accelerator.save(trainer.optimizer.state_dict(),  f\"{model_name}/optimizer.pt\")\n",
        "    \n",
        "    from transformers import FlaxAutoModelForCausalLM\n",
        "    model_flax = FlaxAutoModelForCausalLM.from_pretrained(model_name, from_pt=True)\n",
        "    model_flax.save_pretrained(model_name)\n",
        "    commit_files(model_name, namespace)\n",
        "\n",
        "!rm -rf output/$model_name\n",
        "!rm -rf $model_name"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_t_y81IJhHFV"
      },
      "source": [
        "## Generate lyrics"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lWcDuirw-cRV",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "cellView": "form",
        "outputId": "e3e00b8b-8de1-452e-d5a9-0f8273a95409"
      },
      "source": [
        "# @title Generate\n",
        "#@markdown Enter starting sentence:\n",
        "start = \"I am\" #@param {type:\"string\"}\n",
        "#@markdown Amount of generated texts:\n",
        "num_sequences =  10 #@param {type:\"integer\"}\n",
        "#@markdown Generation settings:\n",
        "min_length =  100 #@param {type:\"integer\"}\n",
        "max_length =   160#@param {type:\"integer\"}\n",
        "temperature = 1 #@param {type:\"slider\", min:0, max:3, step:0.01}\n",
        "top_p = 0.95 #@param {type:\"slider\", min:0, max:1, step:0.01}\n",
        "top_k = 50 #@param {type:\"integer\"}\n",
        "repetition_penalty =  1.0#@param {type:\"number\"}\n",
        "\n",
        "encoded_prompt = tokenizer(start, add_special_tokens=False, return_tensors=\"pt\").input_ids\n",
        "encoded_prompt = encoded_prompt.to(trainer.model.device)\n",
        "# prediction\n",
        "output_sequences = trainer.model.generate(\n",
        "                        input_ids=encoded_prompt,\n",
        "                        max_length=max_length,\n",
        "                        min_length=min_length,\n",
        "                        temperature=float(temperature),\n",
        "                        top_p=float(top_p),\n",
        "                        top_k=int(top_k),\n",
        "                        do_sample=True,\n",
        "                        repetition_penalty=repetition_penalty,\n",
        "                        num_return_sequences=num_sequences\n",
        "                        )\n",
        "# Post-processing\n",
        "predictions = post_process(output_sequences)\n",
        "\n",
        "wandb.log({'examples': wandb.Table(data=[(start, result) for result in predictions], columns=['Input', 'Prediction'])})\n",
        "stylize()\n",
        "table_data = []\n",
        "for result in predictions:\n",
        "  table_data.append('<tr><td>' + get_share_button(get_share_lyrics_url(artist.name, model_name, result)) + '</td><td>' + result.replace(\"\\n\", \"<br>\") + '</td></tr>')\n",
        "display(HTML(share_model_table(artist.name, model_name)))\n",
        "display(HTML(get_table(table_data)))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "    <style>\n",
              "    :root {\n",
              "        --table_bg: #EBF8FF;\n",
              "    }\n",
              "    html[theme=dark] {\n",
              "        --colab-primary-text-color: #d5d5d5;\n",
              "        --table_bg: #2A4365;\n",
              "    }\n",
              "    .jupyter-widgets {\n",
              "        color: var(--colab-primary-text-color);\n",
              "    }\n",
              "    table {\n",
              "        border-collapse: collapse !important;\n",
              "    }\n",
              "    td {\n",
              "        text-align:left !important;\n",
              "        border: solid var(--table_bg) !important;\n",
              "        border-width: 1px 0 !important;\n",
              "        padding: 6px !important;\n",
              "    }\n",
              "    tr:nth-child(even) {\n",
              "        background-color: var(--table_bg) !important;\n",
              "    }\n",
              "    .table_odd {\n",
              "        background-color: var(--table_bg) !important;\n",
              "        margin: 0 !important;\n",
              "    }\n",
              "    .table_even {\n",
              "        border: solid var(--table_bg) !important;\n",
              "        border-width: 1px 0 !important;\n",
              "        margin: 0 !important;\n",
              "    }\n",
              "    .jupyter-widgets {\n",
              "        margin: 6px;\n",
              "    }\n",
              "    .widget-html-content {\n",
              "        font-size: var(--colab-chrome-font-size) !important;\n",
              "        line-height: 1.24 !important;\n",
              "    }\n",
              "    </style>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "</head>\r\n",
              "<body>\r\n",
              "\r\n",
              "<h2></h2>\r\n",
              "\r\n",
              "<table>\r\n",
              "    <colgroup>\r\n",
              "       <col span=\"1\" style=\"width: 10%;\">\r\n",
              "       <col span=\"1\" style=\"width: 100%;\">\r\n",
              "    </colgroup>\r\n",
              "<tr><td>\n",
              "            <div style=\"width: 76px;\">\n",
              "                <a target=\"_blank\" href=\"https://twitter.com/intent/tweet?text=I created an AI bot of Lil Nas X with %23huggingartists!%0APlay with my model or create your own! &url=https://huggingface.co/huggingartists/lil-nas-x\" style='background-color:rgb(27, 149, 224);border-bottom-left-radius:4px;border-bottom-right-radius:4px;border-top-left-radius:4px;border-top-right-radius:4px;box-sizing:border-box;color:rgb(255, 255, 255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\", Arial, sans-serif;font-size:13px;font-stretch:100%;font-style:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;height:28px;line-height:26px;outline-color:rgb(255, 255, 255);outline-style:none;outline-width:0px;padding-bottom:1px;padding-left:9px;padding-right:10px;padding-top:1px;position:relative;text-align:left;text-decoration-color:rgb(255, 255, 255);text-decoration-line:none;text-decoration-style:solid;text-decoration-thickness:auto;user-select:none;vertical-align:top;white-space:nowrap;zoom:1;'>\n",
              "                <i style='background-attachment:scroll;background-clip:border-box;background-color:rgba(0,0,0,0);background-image:url(data:image/svg+xml,%3Csvg%20xmlns%3D%22http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%22%20viewBox%3D%220%200%2072%2072%22%3E%3Cpath%20fill%3D%22none%22%20d%3D%22M0%200h72v72H0z%22%2F%3E%3Cpath%20class%3D%22icon%22%20fill%3D%22%23fff%22%20d%3D%22M68.812%2015.14c-2.348%201.04-4.87%201.744-7.52%202.06%202.704-1.62%204.78-4.186%205.757-7.243-2.53%201.5-5.33%202.592-8.314%203.176C56.35%2010.59%2052.948%209%2049.182%209c-7.23%200-13.092%205.86-13.092%2013.093%200%201.026.118%202.02.338%202.98C25.543%2024.527%2015.9%2019.318%209.44%2011.396c-1.125%201.936-1.77%204.184-1.77%206.58%200%204.543%202.312%208.552%205.824%2010.9-2.146-.07-4.165-.658-5.93-1.64-.002.056-.002.11-.002.163%200%206.345%204.513%2011.638%2010.504%2012.84-1.1.298-2.256.457-3.45.457-.845%200-1.666-.078-2.464-.23%201.667%205.2%206.5%208.985%2012.23%209.09-4.482%203.51-10.13%205.605-16.26%205.605-1.055%200-2.096-.06-3.122-.184%205.794%203.717%2012.676%205.882%2020.067%205.882%2024.083%200%2037.25-19.95%2037.25-37.25%200-.565-.013-1.133-.038-1.693%202.558-1.847%204.778-4.15%206.532-6.774z%22%2F%3E%3C%2Fsvg%3E);background-origin:padding-box;background-position-x:0px;background-position-y:0px;background-repeat-x;background-repeat-y;background-size:auto;color:rgb(255,255,255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\",Arial,sans-serif;font-size:13px;font-stretch:100%;font-style:italic;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;height:18px;line-height:26px;position:relative;text-align:left;text-decoration-thickness:auto;top:4px;user-select:none;white-space:nowrap;width:18px;'></i>\n",
              "                <span style='color:rgb(255,255,255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\",Arial,sans-serif;font-size:13px;font-stretch:100%;font-style:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;line-height:26px;margin-left:4px;text-align:left;text-decoration-thickness:auto;user-select:none;vertical-align:top;white-space:nowrap;zoom:1;'>Tweet</span>\n",
              "            </a>\n",
              "            </div>\n",
              "            </td><td>🎉 Share Lil Nas X model: <a href=\"https://huggingface.co/huggingartists/lil-nas-x\">https://huggingface.co/huggingartists/lil-nas-x</a></td></tr></table>\r\n",
              "\r\n",
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              "</head>\r\n",
              "<body>\r\n",
              "\r\n",
              "<h2></h2>\r\n",
              "\r\n",
              "<table>\r\n",
              "    <colgroup>\r\n",
              "       <col span=\"1\" style=\"width: 10%;\">\r\n",
              "       <col span=\"1\" style=\"width: 100%;\">\r\n",
              "    </colgroup>\r\n",
              "<tr><td>\n",
              "            <div style=\"width: 76px;\">\n",
              "                <a target=\"_blank\" href=\"https://twitter.com/intent/tweet?text=I created an AI bot of Lil Nas X with %23huggingartists!%0A%0ABrand new song:%0AI am not a fan of drugs%0AIve had more sex than cocaine%0AHave sex with my best friends%0AIf I die tomorrow, then you know it%0AYou can never go wrong%0AYoure never alone in the sea of sin%0ARomantic talk, no%0ARomantic talk, no%0ARomantic talk, noI like what you say, Im not your friend%0AWhy you tryna keep me teeny?%0AI dont really care bout what you think, fuck yo dreams, Im not your friend%0AWhy you tryna keep me teeny?%0AI don't really care bout what you think, fuck yo dreams, Im not your friend%0AWhy you tryna keep me teeny?%0AUh, hey,%0A%0APlay with my model or create your own! &url=https://huggingface.co/huggingartists/lil-nas-x\" style='background-color:rgb(27, 149, 224);border-bottom-left-radius:4px;border-bottom-right-radius:4px;border-top-left-radius:4px;border-top-right-radius:4px;box-sizing:border-box;color:rgb(255, 255, 255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\", Arial, sans-serif;font-size:13px;font-stretch:100%;font-style:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;height:28px;line-height:26px;outline-color:rgb(255, 255, 255);outline-style:none;outline-width:0px;padding-bottom:1px;padding-left:9px;padding-right:10px;padding-top:1px;position:relative;text-align:left;text-decoration-color:rgb(255, 255, 255);text-decoration-line:none;text-decoration-style:solid;text-decoration-thickness:auto;user-select:none;vertical-align:top;white-space:nowrap;zoom:1;'>\n",
              "                <i style='background-attachment:scroll;background-clip:border-box;background-color:rgba(0,0,0,0);background-image:url(data:image/svg+xml,%3Csvg%20xmlns%3D%22http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%22%20viewBox%3D%220%200%2072%2072%22%3E%3Cpath%20fill%3D%22none%22%20d%3D%22M0%200h72v72H0z%22%2F%3E%3Cpath%20class%3D%22icon%22%20fill%3D%22%23fff%22%20d%3D%22M68.812%2015.14c-2.348%201.04-4.87%201.744-7.52%202.06%202.704-1.62%204.78-4.186%205.757-7.243-2.53%201.5-5.33%202.592-8.314%203.176C56.35%2010.59%2052.948%209%2049.182%209c-7.23%200-13.092%205.86-13.092%2013.093%200%201.026.118%202.02.338%202.98C25.543%2024.527%2015.9%2019.318%209.44%2011.396c-1.125%201.936-1.77%204.184-1.77%206.58%200%204.543%202.312%208.552%205.824%2010.9-2.146-.07-4.165-.658-5.93-1.64-.002.056-.002.11-.002.163%200%206.345%204.513%2011.638%2010.504%2012.84-1.1.298-2.256.457-3.45.457-.845%200-1.666-.078-2.464-.23%201.667%205.2%206.5%208.985%2012.23%209.09-4.482%203.51-10.13%205.605-16.26%205.605-1.055%200-2.096-.06-3.122-.184%205.794%203.717%2012.676%205.882%2020.067%205.882%2024.083%200%2037.25-19.95%2037.25-37.25%200-.565-.013-1.133-.038-1.693%202.558-1.847%204.778-4.15%206.532-6.774z%22%2F%3E%3C%2Fsvg%3E);background-origin:padding-box;background-position-x:0px;background-position-y:0px;background-repeat-x;background-repeat-y;background-size:auto;color:rgb(255,255,255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\",Arial,sans-serif;font-size:13px;font-stretch:100%;font-style:italic;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;height:18px;line-height:26px;position:relative;text-align:left;text-decoration-thickness:auto;top:4px;user-select:none;white-space:nowrap;width:18px;'></i>\n",
              "                <span style='color:rgb(255,255,255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\",Arial,sans-serif;font-size:13px;font-stretch:100%;font-style:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;line-height:26px;margin-left:4px;text-align:left;text-decoration-thickness:auto;user-select:none;vertical-align:top;white-space:nowrap;zoom:1;'>Tweet</span>\n",
              "            </a>\n",
              "            </div>\n",
              "            </td><td>I am not a fan of drugs<br>Ive had more sex than cocaine<br>Have sex with my best friends<br>If I die tomorrow, then you know it<br>You can never go wrong<br>Youre never alone in the sea of sin<br>Romantic talk, no<br>Romantic talk, no<br>Romantic talk, noI like what you say, Im not your friend<br>Why you tryna keep me teeny?<br>I dont really care bout what you think, fuck yo dreams, Im not your friend<br>Why you tryna keep me teeny?<br>I don't really care bout what you think, fuck yo dreams, Im not your friend<br>Why you tryna keep me teeny?<br>Uh, hey,</td></tr> <tr><td>\n",
              "            <div style=\"width: 76px;\">\n",
              "                <a target=\"_blank\" href=\"https://twitter.com/intent/tweet?text=I created an AI bot of Lil Nas X with %23huggingartists!%0A%0ABrand new song:%0AI am sorry, you might not have been my best self%0ASay to me, am I wrong for wanting you to go up%0ACause you just want me gone%0ASay, am I wrong for wanting you to go up%0ACause you just want me gone%0AI was lied to, I didn't even realize you was a menace%0AI was not looking for you, never cared anyways%0AI said you was the one who needed to be changed, now that you're gone%0AI did not realize how hard it would be to get through these past ups and downs%0AWere we through all that, but now it seems that all the stress%0AYou and me, we must admit, you are the same person%0AI can never go back to that party %0AAnd if I could, I%0A%0APlay with my model or create your own! &url=https://huggingface.co/huggingartists/lil-nas-x\" style='background-color:rgb(27, 149, 224);border-bottom-left-radius:4px;border-bottom-right-radius:4px;border-top-left-radius:4px;border-top-right-radius:4px;box-sizing:border-box;color:rgb(255, 255, 255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\", Arial, sans-serif;font-size:13px;font-stretch:100%;font-style:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;height:28px;line-height:26px;outline-color:rgb(255, 255, 255);outline-style:none;outline-width:0px;padding-bottom:1px;padding-left:9px;padding-right:10px;padding-top:1px;position:relative;text-align:left;text-decoration-color:rgb(255, 255, 255);text-decoration-line:none;text-decoration-style:solid;text-decoration-thickness:auto;user-select:none;vertical-align:top;white-space:nowrap;zoom:1;'>\n",
              "                <i style='background-attachment:scroll;background-clip:border-box;background-color:rgba(0,0,0,0);background-image:url(data:image/svg+xml,%3Csvg%20xmlns%3D%22http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%22%20viewBox%3D%220%200%2072%2072%22%3E%3Cpath%20fill%3D%22none%22%20d%3D%22M0%200h72v72H0z%22%2F%3E%3Cpath%20class%3D%22icon%22%20fill%3D%22%23fff%22%20d%3D%22M68.812%2015.14c-2.348%201.04-4.87%201.744-7.52%202.06%202.704-1.62%204.78-4.186%205.757-7.243-2.53%201.5-5.33%202.592-8.314%203.176C56.35%2010.59%2052.948%209%2049.182%209c-7.23%200-13.092%205.86-13.092%2013.093%200%201.026.118%202.02.338%202.98C25.543%2024.527%2015.9%2019.318%209.44%2011.396c-1.125%201.936-1.77%204.184-1.77%206.58%200%204.543%202.312%208.552%205.824%2010.9-2.146-.07-4.165-.658-5.93-1.64-.002.056-.002.11-.002.163%200%206.345%204.513%2011.638%2010.504%2012.84-1.1.298-2.256.457-3.45.457-.845%200-1.666-.078-2.464-.23%201.667%205.2%206.5%208.985%2012.23%209.09-4.482%203.51-10.13%205.605-16.26%205.605-1.055%200-2.096-.06-3.122-.184%205.794%203.717%2012.676%205.882%2020.067%205.882%2024.083%200%2037.25-19.95%2037.25-37.25%200-.565-.013-1.133-.038-1.693%202.558-1.847%204.778-4.15%206.532-6.774z%22%2F%3E%3C%2Fsvg%3E);background-origin:padding-box;background-position-x:0px;background-position-y:0px;background-repeat-x;background-repeat-y;background-size:auto;color:rgb(255,255,255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\",Arial,sans-serif;font-size:13px;font-stretch:100%;font-style:italic;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;height:18px;line-height:26px;position:relative;text-align:left;text-decoration-thickness:auto;top:4px;user-select:none;white-space:nowrap;width:18px;'></i>\n",
              "                <span style='color:rgb(255,255,255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\",Arial,sans-serif;font-size:13px;font-stretch:100%;font-style:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;line-height:26px;margin-left:4px;text-align:left;text-decoration-thickness:auto;user-select:none;vertical-align:top;white-space:nowrap;zoom:1;'>Tweet</span>\n",
              "            </a>\n",
              "            </div>\n",
              "            </td><td>I am sorry, you might not have been my best self<br>Say to me, am I wrong for wanting you to go up<br>Cause you just want me gone<br>Say, am I wrong for wanting you to go up<br>Cause you just want me gone<br>I was lied to, I didn't even realize you was a menace<br>I was not looking for you, never cared anyways<br>I said you was the one who needed to be changed, now that you're gone<br>I did not realize how hard it would be to get through these past ups and downs<br>Were we through all that, but now it seems that all the stress<br>You and me, we must admit, you are the same person<br>I can never go back to that party <br>And if I could, I</td></tr> <tr><td>\n",
              "            <div style=\"width: 76px;\">\n",
              "                <a target=\"_blank\" href=\"https://twitter.com/intent/tweet?text=I created an AI bot of Lil Nas X with %23huggingartists!%0A%0ABrand new song:%0AI am sorry. Please come here%0AIm okay%0AI dont need you to be so afraid%0AIm a liar Imma break the ice%0ACause now Im tired of waiting for you%0AI said you were friends with me%0ANo need you to be so afraid%0AI said you were friends with me%0ANo need you to be so afraid%0AIma break the ice cause now Im tired of waiting for you%0AIma break the iceCause now Im tired of waiting for youIma break the iceCause now Im tired of waiting for youI say to myself %0AWhy dont you just %0AGive me your hand %0AGive me your hand %0AAint been out in a while anyways%0AGive me your hand %0AAint been out in a while anyways%0AAyy%0A%0APlay with my model or create your own! &url=https://huggingface.co/huggingartists/lil-nas-x\" style='background-color:rgb(27, 149, 224);border-bottom-left-radius:4px;border-bottom-right-radius:4px;border-top-left-radius:4px;border-top-right-radius:4px;box-sizing:border-box;color:rgb(255, 255, 255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\", Arial, sans-serif;font-size:13px;font-stretch:100%;font-style:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;height:28px;line-height:26px;outline-color:rgb(255, 255, 255);outline-style:none;outline-width:0px;padding-bottom:1px;padding-left:9px;padding-right:10px;padding-top:1px;position:relative;text-align:left;text-decoration-color:rgb(255, 255, 255);text-decoration-line:none;text-decoration-style:solid;text-decoration-thickness:auto;user-select:none;vertical-align:top;white-space:nowrap;zoom:1;'>\n",
              "                <i style='background-attachment:scroll;background-clip:border-box;background-color:rgba(0,0,0,0);background-image:url(data:image/svg+xml,%3Csvg%20xmlns%3D%22http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%22%20viewBox%3D%220%200%2072%2072%22%3E%3Cpath%20fill%3D%22none%22%20d%3D%22M0%200h72v72H0z%22%2F%3E%3Cpath%20class%3D%22icon%22%20fill%3D%22%23fff%22%20d%3D%22M68.812%2015.14c-2.348%201.04-4.87%201.744-7.52%202.06%202.704-1.62%204.78-4.186%205.757-7.243-2.53%201.5-5.33%202.592-8.314%203.176C56.35%2010.59%2052.948%209%2049.182%209c-7.23%200-13.092%205.86-13.092%2013.093%200%201.026.118%202.02.338%202.98C25.543%2024.527%2015.9%2019.318%209.44%2011.396c-1.125%201.936-1.77%204.184-1.77%206.58%200%204.543%202.312%208.552%205.824%2010.9-2.146-.07-4.165-.658-5.93-1.64-.002.056-.002.11-.002.163%200%206.345%204.513%2011.638%2010.504%2012.84-1.1.298-2.256.457-3.45.457-.845%200-1.666-.078-2.464-.23%201.667%205.2%206.5%208.985%2012.23%209.09-4.482%203.51-10.13%205.605-16.26%205.605-1.055%200-2.096-.06-3.122-.184%205.794%203.717%2012.676%205.882%2020.067%205.882%2024.083%200%2037.25-19.95%2037.25-37.25%200-.565-.013-1.133-.038-1.693%202.558-1.847%204.778-4.15%206.532-6.774z%22%2F%3E%3C%2Fsvg%3E);background-origin:padding-box;background-position-x:0px;background-position-y:0px;background-repeat-x;background-repeat-y;background-size:auto;color:rgb(255,255,255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\",Arial,sans-serif;font-size:13px;font-stretch:100%;font-style:italic;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;height:18px;line-height:26px;position:relative;text-align:left;text-decoration-thickness:auto;top:4px;user-select:none;white-space:nowrap;width:18px;'></i>\n",
              "                <span style='color:rgb(255,255,255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\",Arial,sans-serif;font-size:13px;font-stretch:100%;font-style:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;line-height:26px;margin-left:4px;text-align:left;text-decoration-thickness:auto;user-select:none;vertical-align:top;white-space:nowrap;zoom:1;'>Tweet</span>\n",
              "            </a>\n",
              "            </div>\n",
              "            </td><td>I am sorry. Please come here<br>Im okay<br>I dont need you to be so afraid<br>Im a liar Imma break the ice<br>Cause now Im tired of waiting for you<br>I said you were friends with me<br>No need you to be so afraid<br>I said you were friends with me<br>No need you to be so afraid<br>Ima break the ice cause now Im tired of waiting for you<br>Ima break the iceCause now Im tired of waiting for youIma break the iceCause now Im tired of waiting for youI say to myself <br>Why dont you just <br>Give me your hand <br>Give me your hand <br>Aint been out in a while anyways<br>Give me your hand <br>Aint been out in a while anyways<br>Ayy</td></tr> <tr><td>\n",
              "            <div style=\"width: 76px;\">\n",
              "                <a target=\"_blank\" href=\"https://twitter.com/intent/tweet?text=I created an AI bot of Lil Nas X with %23huggingartists!%0A%0ABrand new song:%0AI am your guardian angel, yall mad!%0ACome on, I aint really wanting this, just want that %0AI will tell you tonight, this will not be the last timeI see you%0AI cannot leave, I can’t leave no more%0ACarry on, I cannot leave no more%0ALend me your life, for your life, for your life%0ACarry on, I cannot leave%0ALove is what you give it to lose, then take it back%0ATell me you love me in private%0ACall me when you want, call me when you need, call me out by your name%0ACall me by your name, dont you call me by your real name%0AIm not fazed, I only here to sin%0ACall me by your name%0A%0APlay with my model or create your own! &url=https://huggingface.co/huggingartists/lil-nas-x\" style='background-color:rgb(27, 149, 224);border-bottom-left-radius:4px;border-bottom-right-radius:4px;border-top-left-radius:4px;border-top-right-radius:4px;box-sizing:border-box;color:rgb(255, 255, 255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\", Arial, sans-serif;font-size:13px;font-stretch:100%;font-style:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;height:28px;line-height:26px;outline-color:rgb(255, 255, 255);outline-style:none;outline-width:0px;padding-bottom:1px;padding-left:9px;padding-right:10px;padding-top:1px;position:relative;text-align:left;text-decoration-color:rgb(255, 255, 255);text-decoration-line:none;text-decoration-style:solid;text-decoration-thickness:auto;user-select:none;vertical-align:top;white-space:nowrap;zoom:1;'>\n",
              "                <i style='background-attachment:scroll;background-clip:border-box;background-color:rgba(0,0,0,0);background-image:url(data:image/svg+xml,%3Csvg%20xmlns%3D%22http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%22%20viewBox%3D%220%200%2072%2072%22%3E%3Cpath%20fill%3D%22none%22%20d%3D%22M0%200h72v72H0z%22%2F%3E%3Cpath%20class%3D%22icon%22%20fill%3D%22%23fff%22%20d%3D%22M68.812%2015.14c-2.348%201.04-4.87%201.744-7.52%202.06%202.704-1.62%204.78-4.186%205.757-7.243-2.53%201.5-5.33%202.592-8.314%203.176C56.35%2010.59%2052.948%209%2049.182%209c-7.23%200-13.092%205.86-13.092%2013.093%200%201.026.118%202.02.338%202.98C25.543%2024.527%2015.9%2019.318%209.44%2011.396c-1.125%201.936-1.77%204.184-1.77%206.58%200%204.543%202.312%208.552%205.824%2010.9-2.146-.07-4.165-.658-5.93-1.64-.002.056-.002.11-.002.163%200%206.345%204.513%2011.638%2010.504%2012.84-1.1.298-2.256.457-3.45.457-.845%200-1.666-.078-2.464-.23%201.667%205.2%206.5%208.985%2012.23%209.09-4.482%203.51-10.13%205.605-16.26%205.605-1.055%200-2.096-.06-3.122-.184%205.794%203.717%2012.676%205.882%2020.067%205.882%2024.083%200%2037.25-19.95%2037.25-37.25%200-.565-.013-1.133-.038-1.693%202.558-1.847%204.778-4.15%206.532-6.774z%22%2F%3E%3C%2Fsvg%3E);background-origin:padding-box;background-position-x:0px;background-position-y:0px;background-repeat-x;background-repeat-y;background-size:auto;color:rgb(255,255,255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\",Arial,sans-serif;font-size:13px;font-stretch:100%;font-style:italic;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;height:18px;line-height:26px;position:relative;text-align:left;text-decoration-thickness:auto;top:4px;user-select:none;white-space:nowrap;width:18px;'></i>\n",
              "                <span style='color:rgb(255,255,255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\",Arial,sans-serif;font-size:13px;font-stretch:100%;font-style:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;line-height:26px;margin-left:4px;text-align:left;text-decoration-thickness:auto;user-select:none;vertical-align:top;white-space:nowrap;zoom:1;'>Tweet</span>\n",
              "            </a>\n",
              "            </div>\n",
              "            </td><td>I am your guardian angel, yall mad!<br>Come on, I aint really wanting this, just want that <br>I will tell you tonight, this will not be the last timeI see you<br>I cannot leave, I can’t leave no more<br>Carry on, I cannot leave no more<br>Lend me your life, for your life, for your life<br>Carry on, I cannot leave<br>Love is what you give it to lose, then take it back<br>Tell me you love me in private<br>Call me when you want, call me when you need, call me out by your name<br>Call me by your name, dont you call me by your real name<br>Im not fazed, I only here to sin<br>Call me by your name</td></tr> <tr><td>\n",
              "            <div style=\"width: 76px;\">\n",
              "                <a target=\"_blank\" href=\"https://twitter.com/intent/tweet?text=I created an AI bot of Lil Nas X with %23huggingartists!%0A%0ABrand new song:%0AI am sorry to hear that%0ATell your friends, tell your friends%0AI will not lie to get up off that porch%0AMy porch is so cold and I cannot walk alone%0AI will not lie to get up off that porch %0AMerry Christmas, then a chance to kick back and relax%0AThen I can take my horse to the old town road%0AMerry Christmas, then a chance to kick back and relax%0AMerry Christmas, then a chance to kick back and relax%0AI will not lie to get up off that porch%0AI will not lie to get up off that porch %0AMerry Christmas, then a chance to kick back and relax%0AI will not lie to get up off that porch%0AI will not lie to get up off that porch %0AM%0A%0APlay with my model or create your own! &url=https://huggingface.co/huggingartists/lil-nas-x\" style='background-color:rgb(27, 149, 224);border-bottom-left-radius:4px;border-bottom-right-radius:4px;border-top-left-radius:4px;border-top-right-radius:4px;box-sizing:border-box;color:rgb(255, 255, 255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\", Arial, sans-serif;font-size:13px;font-stretch:100%;font-style:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;height:28px;line-height:26px;outline-color:rgb(255, 255, 255);outline-style:none;outline-width:0px;padding-bottom:1px;padding-left:9px;padding-right:10px;padding-top:1px;position:relative;text-align:left;text-decoration-color:rgb(255, 255, 255);text-decoration-line:none;text-decoration-style:solid;text-decoration-thickness:auto;user-select:none;vertical-align:top;white-space:nowrap;zoom:1;'>\n",
              "                <i style='background-attachment:scroll;background-clip:border-box;background-color:rgba(0,0,0,0);background-image:url(data:image/svg+xml,%3Csvg%20xmlns%3D%22http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%22%20viewBox%3D%220%200%2072%2072%22%3E%3Cpath%20fill%3D%22none%22%20d%3D%22M0%200h72v72H0z%22%2F%3E%3Cpath%20class%3D%22icon%22%20fill%3D%22%23fff%22%20d%3D%22M68.812%2015.14c-2.348%201.04-4.87%201.744-7.52%202.06%202.704-1.62%204.78-4.186%205.757-7.243-2.53%201.5-5.33%202.592-8.314%203.176C56.35%2010.59%2052.948%209%2049.182%209c-7.23%200-13.092%205.86-13.092%2013.093%200%201.026.118%202.02.338%202.98C25.543%2024.527%2015.9%2019.318%209.44%2011.396c-1.125%201.936-1.77%204.184-1.77%206.58%200%204.543%202.312%208.552%205.824%2010.9-2.146-.07-4.165-.658-5.93-1.64-.002.056-.002.11-.002.163%200%206.345%204.513%2011.638%2010.504%2012.84-1.1.298-2.256.457-3.45.457-.845%200-1.666-.078-2.464-.23%201.667%205.2%206.5%208.985%2012.23%209.09-4.482%203.51-10.13%205.605-16.26%205.605-1.055%200-2.096-.06-3.122-.184%205.794%203.717%2012.676%205.882%2020.067%205.882%2024.083%200%2037.25-19.95%2037.25-37.25%200-.565-.013-1.133-.038-1.693%202.558-1.847%204.778-4.15%206.532-6.774z%22%2F%3E%3C%2Fsvg%3E);background-origin:padding-box;background-position-x:0px;background-position-y:0px;background-repeat-x;background-repeat-y;background-size:auto;color:rgb(255,255,255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\",Arial,sans-serif;font-size:13px;font-stretch:100%;font-style:italic;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;height:18px;line-height:26px;position:relative;text-align:left;text-decoration-thickness:auto;top:4px;user-select:none;white-space:nowrap;width:18px;'></i>\n",
              "                <span style='color:rgb(255,255,255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\",Arial,sans-serif;font-size:13px;font-stretch:100%;font-style:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;line-height:26px;margin-left:4px;text-align:left;text-decoration-thickness:auto;user-select:none;vertical-align:top;white-space:nowrap;zoom:1;'>Tweet</span>\n",
              "            </a>\n",
              "            </div>\n",
              "            </td><td>I am sorry to hear that<br>Tell your friends, tell your friends<br>I will not lie to get up off that porch<br>My porch is so cold and I cannot walk alone<br>I will not lie to get up off that porch <br>Merry Christmas, then a chance to kick back and relax<br>Then I can take my horse to the old town road<br>Merry Christmas, then a chance to kick back and relax<br>Merry Christmas, then a chance to kick back and relax<br>I will not lie to get up off that porch<br>I will not lie to get up off that porch <br>Merry Christmas, then a chance to kick back and relax<br>I will not lie to get up off that porch<br>I will not lie to get up off that porch <br>M</td></tr> <tr><td>\n",
              "            <div style=\"width: 76px;\">\n",
              "                <a target=\"_blank\" href=\"https://twitter.com/intent/tweet?text=I created an AI bot of Lil Nas X with %23huggingartists!%0A%0ABrand new song:%0AI am not yours%0AYou may not be mine, but I am your%0AFuck that shit bitch %0ARun away, swim in the ocean%0ASee ya, Im cute, do your niggas a favor%0AThought you wanted me to stay with you%0ANiggas gonna sue me if I touch that pussy%0AI dont need your pussy, its fine%0AI dont need your pussy, its fine %0AFuck that shit bitch %0ARun away, swim in the oceanSee ya, Im cute, do your niggas a favor%0AThought you wanted me to stay with you%0ANiggas gonna sue me if I touch that pussy%0AI dont need your pussy, its fine%0AI dont need your pussy, its fine %0AFuck that shit bitch %0ARun%0A%0APlay with my model or create your own! &url=https://huggingface.co/huggingartists/lil-nas-x\" style='background-color:rgb(27, 149, 224);border-bottom-left-radius:4px;border-bottom-right-radius:4px;border-top-left-radius:4px;border-top-right-radius:4px;box-sizing:border-box;color:rgb(255, 255, 255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\", Arial, sans-serif;font-size:13px;font-stretch:100%;font-style:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;height:28px;line-height:26px;outline-color:rgb(255, 255, 255);outline-style:none;outline-width:0px;padding-bottom:1px;padding-left:9px;padding-right:10px;padding-top:1px;position:relative;text-align:left;text-decoration-color:rgb(255, 255, 255);text-decoration-line:none;text-decoration-style:solid;text-decoration-thickness:auto;user-select:none;vertical-align:top;white-space:nowrap;zoom:1;'>\n",
              "                <i style='background-attachment:scroll;background-clip:border-box;background-color:rgba(0,0,0,0);background-image:url(data:image/svg+xml,%3Csvg%20xmlns%3D%22http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%22%20viewBox%3D%220%200%2072%2072%22%3E%3Cpath%20fill%3D%22none%22%20d%3D%22M0%200h72v72H0z%22%2F%3E%3Cpath%20class%3D%22icon%22%20fill%3D%22%23fff%22%20d%3D%22M68.812%2015.14c-2.348%201.04-4.87%201.744-7.52%202.06%202.704-1.62%204.78-4.186%205.757-7.243-2.53%201.5-5.33%202.592-8.314%203.176C56.35%2010.59%2052.948%209%2049.182%209c-7.23%200-13.092%205.86-13.092%2013.093%200%201.026.118%202.02.338%202.98C25.543%2024.527%2015.9%2019.318%209.44%2011.396c-1.125%201.936-1.77%204.184-1.77%206.58%200%204.543%202.312%208.552%205.824%2010.9-2.146-.07-4.165-.658-5.93-1.64-.002.056-.002.11-.002.163%200%206.345%204.513%2011.638%2010.504%2012.84-1.1.298-2.256.457-3.45.457-.845%200-1.666-.078-2.464-.23%201.667%205.2%206.5%208.985%2012.23%209.09-4.482%203.51-10.13%205.605-16.26%205.605-1.055%200-2.096-.06-3.122-.184%205.794%203.717%2012.676%205.882%2020.067%205.882%2024.083%200%2037.25-19.95%2037.25-37.25%200-.565-.013-1.133-.038-1.693%202.558-1.847%204.778-4.15%206.532-6.774z%22%2F%3E%3C%2Fsvg%3E);background-origin:padding-box;background-position-x:0px;background-position-y:0px;background-repeat-x;background-repeat-y;background-size:auto;color:rgb(255,255,255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\",Arial,sans-serif;font-size:13px;font-stretch:100%;font-style:italic;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;height:18px;line-height:26px;position:relative;text-align:left;text-decoration-thickness:auto;top:4px;user-select:none;white-space:nowrap;width:18px;'></i>\n",
              "                <span style='color:rgb(255,255,255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\",Arial,sans-serif;font-size:13px;font-stretch:100%;font-style:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;line-height:26px;margin-left:4px;text-align:left;text-decoration-thickness:auto;user-select:none;vertical-align:top;white-space:nowrap;zoom:1;'>Tweet</span>\n",
              "            </a>\n",
              "            </div>\n",
              "            </td><td>I am not yours<br>You may not be mine, but I am your<br>Fuck that shit bitch <br>Run away, swim in the ocean<br>See ya, Im cute, do your niggas a favor<br>Thought you wanted me to stay with you<br>Niggas gonna sue me if I touch that pussy<br>I dont need your pussy, its fine<br>I dont need your pussy, its fine <br>Fuck that shit bitch <br>Run away, swim in the oceanSee ya, Im cute, do your niggas a favor<br>Thought you wanted me to stay with you<br>Niggas gonna sue me if I touch that pussy<br>I dont need your pussy, its fine<br>I dont need your pussy, its fine <br>Fuck that shit bitch <br>Run</td></tr> <tr><td>\n",
              "            <div style=\"width: 76px;\">\n",
              "                <a target=\"_blank\" href=\"https://twitter.com/intent/tweet?text=I created an AI bot of Lil Nas X with %23huggingartists!%0A%0ABrand new song:%0AI am sorry I didnthin%0AI know whats up nigga, you fuckin gettin low, cause I gotta do it%0AGet your soldiers up, I gotta do it%0AGet your soldiers up, I gotta do it %0AGet your soldiers up, I gotta do it %0AGet your soldiers up, I gotta do it%0AGet your soldiers up, I gotta do it %0AGet your soldiers up, I gotta do it %0AGet your soldiers up%0A%0APlay with my model or create your own! &url=https://huggingface.co/huggingartists/lil-nas-x\" style='background-color:rgb(27, 149, 224);border-bottom-left-radius:4px;border-bottom-right-radius:4px;border-top-left-radius:4px;border-top-right-radius:4px;box-sizing:border-box;color:rgb(255, 255, 255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\", Arial, sans-serif;font-size:13px;font-stretch:100%;font-style:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;height:28px;line-height:26px;outline-color:rgb(255, 255, 255);outline-style:none;outline-width:0px;padding-bottom:1px;padding-left:9px;padding-right:10px;padding-top:1px;position:relative;text-align:left;text-decoration-color:rgb(255, 255, 255);text-decoration-line:none;text-decoration-style:solid;text-decoration-thickness:auto;user-select:none;vertical-align:top;white-space:nowrap;zoom:1;'>\n",
              "                <i style='background-attachment:scroll;background-clip:border-box;background-color:rgba(0,0,0,0);background-image:url(data:image/svg+xml,%3Csvg%20xmlns%3D%22http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%22%20viewBox%3D%220%200%2072%2072%22%3E%3Cpath%20fill%3D%22none%22%20d%3D%22M0%200h72v72H0z%22%2F%3E%3Cpath%20class%3D%22icon%22%20fill%3D%22%23fff%22%20d%3D%22M68.812%2015.14c-2.348%201.04-4.87%201.744-7.52%202.06%202.704-1.62%204.78-4.186%205.757-7.243-2.53%201.5-5.33%202.592-8.314%203.176C56.35%2010.59%2052.948%209%2049.182%209c-7.23%200-13.092%205.86-13.092%2013.093%200%201.026.118%202.02.338%202.98C25.543%2024.527%2015.9%2019.318%209.44%2011.396c-1.125%201.936-1.77%204.184-1.77%206.58%200%204.543%202.312%208.552%205.824%2010.9-2.146-.07-4.165-.658-5.93-1.64-.002.056-.002.11-.002.163%200%206.345%204.513%2011.638%2010.504%2012.84-1.1.298-2.256.457-3.45.457-.845%200-1.666-.078-2.464-.23%201.667%205.2%206.5%208.985%2012.23%209.09-4.482%203.51-10.13%205.605-16.26%205.605-1.055%200-2.096-.06-3.122-.184%205.794%203.717%2012.676%205.882%2020.067%205.882%2024.083%200%2037.25-19.95%2037.25-37.25%200-.565-.013-1.133-.038-1.693%202.558-1.847%204.778-4.15%206.532-6.774z%22%2F%3E%3C%2Fsvg%3E);background-origin:padding-box;background-position-x:0px;background-position-y:0px;background-repeat-x;background-repeat-y;background-size:auto;color:rgb(255,255,255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\",Arial,sans-serif;font-size:13px;font-stretch:100%;font-style:italic;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;height:18px;line-height:26px;position:relative;text-align:left;text-decoration-thickness:auto;top:4px;user-select:none;white-space:nowrap;width:18px;'></i>\n",
              "                <span style='color:rgb(255,255,255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\",Arial,sans-serif;font-size:13px;font-stretch:100%;font-style:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;line-height:26px;margin-left:4px;text-align:left;text-decoration-thickness:auto;user-select:none;vertical-align:top;white-space:nowrap;zoom:1;'>Tweet</span>\n",
              "            </a>\n",
              "            </div>\n",
              "            </td><td>I am sorry I didnthin<br>I know whats up nigga, you fuckin gettin low, cause I gotta do it<br>Get your soldiers up, I gotta do it<br>Get your soldiers up, I gotta do it <br>Get your soldiers up, I gotta do it <br>Get your soldiers up, I gotta do it<br>Get your soldiers up, I gotta do it <br>Get your soldiers up, I gotta do it <br>Get your soldiers up</td></tr> <tr><td>\n",
              "            <div style=\"width: 76px;\">\n",
              "                <a target=\"_blank\" href=\"https://twitter.com/intent/tweet?text=I created an AI bot of Lil Nas X with %23huggingartists!%0A%0ABrand new song:%0AI am sorry I made you feel bad, I know that hurt, and I must admit it hurts%0AI cannot take no more from you, baby%0AI cannot let you down, I know that you need to%0AI cannot take no more from you, baby%0AI cannot take no more from you, baby%0AWhat I need from you, baby%0AYou live on the run, you can catch me on the freeway%0AYou can whip your Porsche and go, only God will let you go%0AStop the violence, stop the drugs, stop the violence%0AStop the rumors, stop the drugs, stop the violence%0AStop the war, stop the pill, stop the violence%0AStop the menace, stop the drugs%0AStop the menace, stop the drugs%0AStop the drugs, stop the violence%0A%0APlay with my model or create your own! &url=https://huggingface.co/huggingartists/lil-nas-x\" style='background-color:rgb(27, 149, 224);border-bottom-left-radius:4px;border-bottom-right-radius:4px;border-top-left-radius:4px;border-top-right-radius:4px;box-sizing:border-box;color:rgb(255, 255, 255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\", Arial, sans-serif;font-size:13px;font-stretch:100%;font-style:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;height:28px;line-height:26px;outline-color:rgb(255, 255, 255);outline-style:none;outline-width:0px;padding-bottom:1px;padding-left:9px;padding-right:10px;padding-top:1px;position:relative;text-align:left;text-decoration-color:rgb(255, 255, 255);text-decoration-line:none;text-decoration-style:solid;text-decoration-thickness:auto;user-select:none;vertical-align:top;white-space:nowrap;zoom:1;'>\n",
              "                <i style='background-attachment:scroll;background-clip:border-box;background-color:rgba(0,0,0,0);background-image:url(data:image/svg+xml,%3Csvg%20xmlns%3D%22http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%22%20viewBox%3D%220%200%2072%2072%22%3E%3Cpath%20fill%3D%22none%22%20d%3D%22M0%200h72v72H0z%22%2F%3E%3Cpath%20class%3D%22icon%22%20fill%3D%22%23fff%22%20d%3D%22M68.812%2015.14c-2.348%201.04-4.87%201.744-7.52%202.06%202.704-1.62%204.78-4.186%205.757-7.243-2.53%201.5-5.33%202.592-8.314%203.176C56.35%2010.59%2052.948%209%2049.182%209c-7.23%200-13.092%205.86-13.092%2013.093%200%201.026.118%202.02.338%202.98C25.543%2024.527%2015.9%2019.318%209.44%2011.396c-1.125%201.936-1.77%204.184-1.77%206.58%200%204.543%202.312%208.552%205.824%2010.9-2.146-.07-4.165-.658-5.93-1.64-.002.056-.002.11-.002.163%200%206.345%204.513%2011.638%2010.504%2012.84-1.1.298-2.256.457-3.45.457-.845%200-1.666-.078-2.464-.23%201.667%205.2%206.5%208.985%2012.23%209.09-4.482%203.51-10.13%205.605-16.26%205.605-1.055%200-2.096-.06-3.122-.184%205.794%203.717%2012.676%205.882%2020.067%205.882%2024.083%200%2037.25-19.95%2037.25-37.25%200-.565-.013-1.133-.038-1.693%202.558-1.847%204.778-4.15%206.532-6.774z%22%2F%3E%3C%2Fsvg%3E);background-origin:padding-box;background-position-x:0px;background-position-y:0px;background-repeat-x;background-repeat-y;background-size:auto;color:rgb(255,255,255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\",Arial,sans-serif;font-size:13px;font-stretch:100%;font-style:italic;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;height:18px;line-height:26px;position:relative;text-align:left;text-decoration-thickness:auto;top:4px;user-select:none;white-space:nowrap;width:18px;'></i>\n",
              "                <span style='color:rgb(255,255,255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\",Arial,sans-serif;font-size:13px;font-stretch:100%;font-style:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;line-height:26px;margin-left:4px;text-align:left;text-decoration-thickness:auto;user-select:none;vertical-align:top;white-space:nowrap;zoom:1;'>Tweet</span>\n",
              "            </a>\n",
              "            </div>\n",
              "            </td><td>I am sorry I made you feel bad, I know that hurt, and I must admit it hurts<br>I cannot take no more from you, baby<br>I cannot let you down, I know that you need to<br>I cannot take no more from you, baby<br>I cannot take no more from you, baby<br>What I need from you, baby<br>You live on the run, you can catch me on the freeway<br>You can whip your Porsche and go, only God will let you go<br>Stop the violence, stop the drugs, stop the violence<br>Stop the rumors, stop the drugs, stop the violence<br>Stop the war, stop the pill, stop the violence<br>Stop the menace, stop the drugs<br>Stop the menace, stop the drugs<br>Stop the drugs, stop the violence</td></tr> <tr><td>\n",
              "            <div style=\"width: 76px;\">\n",
              "                <a target=\"_blank\" href=\"https://twitter.com/intent/tweet?text=I created an AI bot of Lil Nas X with %23huggingartists!%0A%0ABrand new song:%0AI am a menace to be reckoned with%0AI am not your type %0AYoull love me %0ABitch, don’t try to take’ you down%0AIf you did, you would probably know %0AWhen I walk alone in my all white Nikes%0AStuck on the road like I missed my flight%0AStuck on my bike like I missed my flight%0AStuck on my hood like I missed my home%0AThats how I feel about you now%0AI walked alone in my all white Nikes%0AStuck on the road like I missed my flight%0AStuck on my bike like I missed my home%0AThats how I feel about you now%0AI know all of this and its all in the back%0AI cant be around you no more%0A%0APlay with my model or create your own! &url=https://huggingface.co/huggingartists/lil-nas-x\" style='background-color:rgb(27, 149, 224);border-bottom-left-radius:4px;border-bottom-right-radius:4px;border-top-left-radius:4px;border-top-right-radius:4px;box-sizing:border-box;color:rgb(255, 255, 255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\", Arial, sans-serif;font-size:13px;font-stretch:100%;font-style:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;height:28px;line-height:26px;outline-color:rgb(255, 255, 255);outline-style:none;outline-width:0px;padding-bottom:1px;padding-left:9px;padding-right:10px;padding-top:1px;position:relative;text-align:left;text-decoration-color:rgb(255, 255, 255);text-decoration-line:none;text-decoration-style:solid;text-decoration-thickness:auto;user-select:none;vertical-align:top;white-space:nowrap;zoom:1;'>\n",
              "                <i style='background-attachment:scroll;background-clip:border-box;background-color:rgba(0,0,0,0);background-image:url(data:image/svg+xml,%3Csvg%20xmlns%3D%22http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%22%20viewBox%3D%220%200%2072%2072%22%3E%3Cpath%20fill%3D%22none%22%20d%3D%22M0%200h72v72H0z%22%2F%3E%3Cpath%20class%3D%22icon%22%20fill%3D%22%23fff%22%20d%3D%22M68.812%2015.14c-2.348%201.04-4.87%201.744-7.52%202.06%202.704-1.62%204.78-4.186%205.757-7.243-2.53%201.5-5.33%202.592-8.314%203.176C56.35%2010.59%2052.948%209%2049.182%209c-7.23%200-13.092%205.86-13.092%2013.093%200%201.026.118%202.02.338%202.98C25.543%2024.527%2015.9%2019.318%209.44%2011.396c-1.125%201.936-1.77%204.184-1.77%206.58%200%204.543%202.312%208.552%205.824%2010.9-2.146-.07-4.165-.658-5.93-1.64-.002.056-.002.11-.002.163%200%206.345%204.513%2011.638%2010.504%2012.84-1.1.298-2.256.457-3.45.457-.845%200-1.666-.078-2.464-.23%201.667%205.2%206.5%208.985%2012.23%209.09-4.482%203.51-10.13%205.605-16.26%205.605-1.055%200-2.096-.06-3.122-.184%205.794%203.717%2012.676%205.882%2020.067%205.882%2024.083%200%2037.25-19.95%2037.25-37.25%200-.565-.013-1.133-.038-1.693%202.558-1.847%204.778-4.15%206.532-6.774z%22%2F%3E%3C%2Fsvg%3E);background-origin:padding-box;background-position-x:0px;background-position-y:0px;background-repeat-x;background-repeat-y;background-size:auto;color:rgb(255,255,255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\",Arial,sans-serif;font-size:13px;font-stretch:100%;font-style:italic;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;height:18px;line-height:26px;position:relative;text-align:left;text-decoration-thickness:auto;top:4px;user-select:none;white-space:nowrap;width:18px;'></i>\n",
              "                <span style='color:rgb(255,255,255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\",Arial,sans-serif;font-size:13px;font-stretch:100%;font-style:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;line-height:26px;margin-left:4px;text-align:left;text-decoration-thickness:auto;user-select:none;vertical-align:top;white-space:nowrap;zoom:1;'>Tweet</span>\n",
              "            </a>\n",
              "            </div>\n",
              "            </td><td>I am a menace to be reckoned with<br>I am not your type <br>Youll love me <br>Bitch, don’t try to take’ you down<br>If you did, you would probably know <br>When I walk alone in my all white Nikes<br>Stuck on the road like I missed my flight<br>Stuck on my bike like I missed my flight<br>Stuck on my hood like I missed my home<br>Thats how I feel about you now<br>I walked alone in my all white Nikes<br>Stuck on the road like I missed my flight<br>Stuck on my bike like I missed my home<br>Thats how I feel about you now<br>I know all of this and its all in the back<br>I cant be around you no more</td></tr> <tr><td>\n",
              "            <div style=\"width: 76px;\">\n",
              "                <a target=\"_blank\" href=\"https://twitter.com/intent/tweet?text=I created an AI bot of Lil Nas X with %23huggingartists!%0A%0ABrand new song:%0AI am%0AAnd theres no reason not to do it%0AIm gonna take my horse to the old town road%0AIm gonna ride til I cant no more%0AIm gonna take my horse to the old town road%0AIm gonna ride til I cant no moreLil Nas%0ABaby, you aint got no love lost in this%0AYou know how I feel like %0AAnd I know this is all for niggas to deal with%0ABut Im gon take my horse to the old town road%0AIm gonna ride til I cant no moreIm gonna take my horse to the old town road%0AIm gonna ride til I cant no moreIll take my horse to the old town road%0AIm gonna ride til I cant no more%0AIll take my horse to the old town road%0AIll take%0A%0APlay with my model or create your own! &url=https://huggingface.co/huggingartists/lil-nas-x\" style='background-color:rgb(27, 149, 224);border-bottom-left-radius:4px;border-bottom-right-radius:4px;border-top-left-radius:4px;border-top-right-radius:4px;box-sizing:border-box;color:rgb(255, 255, 255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\", Arial, sans-serif;font-size:13px;font-stretch:100%;font-style:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;height:28px;line-height:26px;outline-color:rgb(255, 255, 255);outline-style:none;outline-width:0px;padding-bottom:1px;padding-left:9px;padding-right:10px;padding-top:1px;position:relative;text-align:left;text-decoration-color:rgb(255, 255, 255);text-decoration-line:none;text-decoration-style:solid;text-decoration-thickness:auto;user-select:none;vertical-align:top;white-space:nowrap;zoom:1;'>\n",
              "                <i style='background-attachment:scroll;background-clip:border-box;background-color:rgba(0,0,0,0);background-image:url(data:image/svg+xml,%3Csvg%20xmlns%3D%22http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%22%20viewBox%3D%220%200%2072%2072%22%3E%3Cpath%20fill%3D%22none%22%20d%3D%22M0%200h72v72H0z%22%2F%3E%3Cpath%20class%3D%22icon%22%20fill%3D%22%23fff%22%20d%3D%22M68.812%2015.14c-2.348%201.04-4.87%201.744-7.52%202.06%202.704-1.62%204.78-4.186%205.757-7.243-2.53%201.5-5.33%202.592-8.314%203.176C56.35%2010.59%2052.948%209%2049.182%209c-7.23%200-13.092%205.86-13.092%2013.093%200%201.026.118%202.02.338%202.98C25.543%2024.527%2015.9%2019.318%209.44%2011.396c-1.125%201.936-1.77%204.184-1.77%206.58%200%204.543%202.312%208.552%205.824%2010.9-2.146-.07-4.165-.658-5.93-1.64-.002.056-.002.11-.002.163%200%206.345%204.513%2011.638%2010.504%2012.84-1.1.298-2.256.457-3.45.457-.845%200-1.666-.078-2.464-.23%201.667%205.2%206.5%208.985%2012.23%209.09-4.482%203.51-10.13%205.605-16.26%205.605-1.055%200-2.096-.06-3.122-.184%205.794%203.717%2012.676%205.882%2020.067%205.882%2024.083%200%2037.25-19.95%2037.25-37.25%200-.565-.013-1.133-.038-1.693%202.558-1.847%204.778-4.15%206.532-6.774z%22%2F%3E%3C%2Fsvg%3E);background-origin:padding-box;background-position-x:0px;background-position-y:0px;background-repeat-x;background-repeat-y;background-size:auto;color:rgb(255,255,255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\",Arial,sans-serif;font-size:13px;font-stretch:100%;font-style:italic;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;height:18px;line-height:26px;position:relative;text-align:left;text-decoration-thickness:auto;top:4px;user-select:none;white-space:nowrap;width:18px;'></i>\n",
              "                <span style='color:rgb(255,255,255);cursor:pointer;display:inline-block;font-family:\"Helvetica Neue\",Arial,sans-serif;font-size:13px;font-stretch:100%;font-style:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;line-height:26px;margin-left:4px;text-align:left;text-decoration-thickness:auto;user-select:none;vertical-align:top;white-space:nowrap;zoom:1;'>Tweet</span>\n",
              "            </a>\n",
              "            </div>\n",
              "            </td><td>I am<br>And theres no reason not to do it<br>Im gonna take my horse to the old town road<br>Im gonna ride til I cant no more<br>Im gonna take my horse to the old town road<br>Im gonna ride til I cant no moreLil Nas<br>Baby, you aint got no love lost in this<br>You know how I feel like <br>And I know this is all for niggas to deal with<br>But Im gon take my horse to the old town road<br>Im gonna ride til I cant no moreIm gonna take my horse to the old town road<br>Im gonna ride til I cant no moreIll take my horse to the old town road<br>Im gonna ride til I cant no more<br>Ill take my horse to the old town road<br>Ill take</td></tr></table>\r\n",
              "\r\n",
              "</body>\r\n",
              "</html>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
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          "metadata": {
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    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SGglGxLtNyjk"
      },
      "source": [
        "## About\n",
        "\n",
        "*Built by Aleksey Korshuk*\n",
        "\n",
        "[![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk)\n",
        "\n",
        "[![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk)\n",
        "\n",
        "🚀 If you want to contribute to this project OR create something cool together — contact me: [link](https://github.com/AlekseyKorshuk)\n",
        "\n",
        "For more details, visit the project repository:\n",
        "\n",
        "[![GitHub stars](https://img.shields.io/github/stars/AlekseyKorshuk/huggingartists?style=social)](https://github.com/AlekseyKorshuk/huggingartists)\n",
        "\n",
        "**Disclaimer: this project is not to be used to publish any false generated information or unpleasant words but to perform research on Natural Language Generation.**\n",
        "\n",
        "## Resources\n",
        "* Inspired by [HuggingTweets](https://github.com/borisdayma/huggingtweets)\n",
        "* [Explore the W&B report](https://wandb.ai/huggingartists/huggingartists/reportlist) to understand how the model works\n",
        "* [HuggingFace and W&B integration documentation](https://docs.wandb.com/library/integrations/huggingface)\n",
        "\n",
        "## Got questions about W&B?\n",
        "If you have any questions about using W&B to track your model performance and predictions, please reach out to the [slack community](https://wb-forum.slack.com/signup#/)."
      ]
    }
  ]
}