Autodetect llamacpp_HF loader when tokenizer exists

Author: oobabooga

modules/models.py

@@ -257,7 +257,7 @@ def llamacpp_HF_loader(model_name):
     path = Path(f'{shared.args.model_dir}/{model_name}')
 
     # Check if a HF tokenizer is available for the model
-    if all((path / file).exists() for file in ['tokenizer.json', 'tokenizer_config.json']):
+    if all((path / file).exists() for file in ['tokenizer_config.json']):
         logger.info(f'Using tokenizer from: \"{path}\"')
     else:
         logger.error("Could not load the model because a tokenizer in Transformers format was not found.")

modules/models_settings.py

@@ -153,6 +153,8 @@ def infer_loader(model_name, model_settings):
         loader = 'ExLlamav2_HF'
     elif (path_to_model / 'quant_config.json').exists() or re.match(r'.*-awq', model_name.lower()):
         loader = 'AutoAWQ'
+    elif len(list(path_to_model.glob('*.gguf'))) > 0 and path_to_model.is_dir() and (path_to_model / 'tokenizer_config.json').exists():
+        loader = 'llamacpp_HF'
     elif len(list(path_to_model.glob('*.gguf'))) > 0:
         loader = 'llama.cpp'
     elif re.match(r'.*\.gguf', model_name.lower()):
@@ -225,7 +227,7 @@ def apply_model_settings_to_state(model, state):
         loader = model_settings.pop('loader')
 
         # If the user is using an alternative loader for the same model type, let them keep using it
-        if not (loader == 'ExLlamav2_HF' and state['loader'] in ['GPTQ-for-LLaMa', 'ExLlamav2', 'AutoGPTQ']) and not (loader == 'llama.cpp' and state['loader'] in ['llamacpp_HF', 'ctransformers']):
+        if not (loader == 'ExLlamav2_HF' and state['loader'] in ['GPTQ-for-LLaMa', 'ExLlamav2', 'AutoGPTQ']) and not (loader == 'llama.cpp' and state['loader'] in ['ctransformers']):
             state['loader'] = loader
 
     for k in model_settings: