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https://github.com/oobabooga/text-generation-webui.git
synced 2024-10-01 01:26:03 -04:00
Minor logging improvements
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@ -54,7 +54,7 @@ sampler_hijack.hijack_samplers()
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def load_model(model_name, loader=None):
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def load_model(model_name, loader=None):
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logger.info(f"Loading {model_name}")
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logger.info(f"Loading \"{model_name}\"")
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t0 = time.time()
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t0 = time.time()
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shared.is_seq2seq = False
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shared.is_seq2seq = False
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@ -246,7 +246,7 @@ def llamacpp_loader(model_name):
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else:
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else:
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model_file = list(Path(f'{shared.args.model_dir}/{model_name}').glob('*.gguf'))[0]
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model_file = list(Path(f'{shared.args.model_dir}/{model_name}').glob('*.gguf'))[0]
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logger.info(f"llama.cpp weights detected: {model_file}")
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logger.info(f"llama.cpp weights detected: \"{model_file}\"")
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model, tokenizer = LlamaCppModel.from_pretrained(model_file)
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model, tokenizer = LlamaCppModel.from_pretrained(model_file)
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return model, tokenizer
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return model, tokenizer
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@ -257,7 +257,7 @@ def llamacpp_HF_loader(model_name):
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for fname in [model_name, "oobabooga_llama-tokenizer", "llama-tokenizer"]:
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for fname in [model_name, "oobabooga_llama-tokenizer", "llama-tokenizer"]:
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path = Path(f'{shared.args.model_dir}/{fname}')
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path = Path(f'{shared.args.model_dir}/{fname}')
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if all((path / file).exists() for file in ['tokenizer_config.json', 'special_tokens_map.json', 'tokenizer.model']):
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if all((path / file).exists() for file in ['tokenizer_config.json', 'special_tokens_map.json', 'tokenizer.model']):
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logger.info(f'Using tokenizer from: {path}')
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logger.info(f'Using tokenizer from: \"{path}\"')
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break
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break
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else:
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else:
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logger.error("Could not load the model because a tokenizer in transformers format was not found. Please download oobabooga/llama-tokenizer.")
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logger.error("Could not load the model because a tokenizer in transformers format was not found. Please download oobabooga/llama-tokenizer.")
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@ -298,7 +298,7 @@ def ctransformers_loader(model_name):
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logger.error("Could not find a model for ctransformers.")
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logger.error("Could not find a model for ctransformers.")
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return None, None
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return None, None
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logger.info(f'ctransformers weights detected: {model_file}')
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logger.info(f'ctransformers weights detected: \"{model_file}\"')
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model, tokenizer = ctrans.from_pretrained(model_file)
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model, tokenizer = ctrans.from_pretrained(model_file)
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return model, tokenizer
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return model, tokenizer
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@ -393,7 +393,7 @@ def HQQ_loader(model_name):
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from hqq.core.quantize import HQQBackend, HQQLinear
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from hqq.core.quantize import HQQBackend, HQQLinear
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from hqq.engine.hf import HQQModelForCausalLM
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from hqq.engine.hf import HQQModelForCausalLM
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logger.info(f"Loading HQQ model with backend: {shared.args.hqq_backend}")
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logger.info(f"Loading HQQ model with backend: \"{shared.args.hqq_backend}\"")
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model_dir = Path(f'{shared.args.model_dir}/{model_name}')
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model_dir = Path(f'{shared.args.model_dir}/{model_name}')
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model = HQQModelForCausalLM.from_quantized(str(model_dir))
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model = HQQModelForCausalLM.from_quantized(str(model_dir))
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@ -187,7 +187,7 @@ if __name__ == "__main__":
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settings_file = Path('settings.json')
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settings_file = Path('settings.json')
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if settings_file is not None:
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if settings_file is not None:
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logger.info(f"Loading settings from {settings_file}")
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logger.info(f"Loading settings from \"{settings_file}\"")
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file_contents = open(settings_file, 'r', encoding='utf-8').read()
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file_contents = open(settings_file, 'r', encoding='utf-8').read()
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new_settings = json.loads(file_contents) if settings_file.suffix == "json" else yaml.safe_load(file_contents)
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new_settings = json.loads(file_contents) if settings_file.suffix == "json" else yaml.safe_load(file_contents)
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shared.settings.update(new_settings)
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shared.settings.update(new_settings)
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