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An enhanced mini-GPT based on Stanford CS224N Assignment

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Mini_GPT

Adopted from Assignment from course CS224N, Stanford University

This GPT-1-like model is highly simplified and designed to predict the origin of a target based on a given corpus. (Pre-)Training objectives of current GPT models, except random deletion, are dropped to compact the training.

Main Directory

environment.yml / .environment_gpu.yml: Environments for cpu and gpu

run.py / run.sh: .py and .sh runfiles

Model folder

.MiniGPT: helper module, call all classes

.model: the GPT-1 class

.helper: an organizer class for methods to run training, pretraining and finetuning to update GPT from .model

.dataset: Class for methods to prepare normal or span-corrupted training datasets

.attention: Classes for two multi-head self-attention methods (vanila and synthesizers)

.trainer: Classes for training method

.utils: Classes for predictions and evaluations methods

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