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45 lines
1.4 KiB
Python
45 lines
1.4 KiB
Python
from pathlib import Path
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from auto_gptq import AutoGPTQForCausalLM
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import modules.shared as shared
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from modules.logging_colors import logger
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from modules.models import get_max_memory_dict
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def load_quantized(model_name):
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path_to_model = Path(f'{shared.args.model_dir}/{model_name}')
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pt_path = None
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use_safetensors = False
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# Find the model checkpoint
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for ext in ['.safetensors', '.pt', '.bin']:
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found = list(path_to_model.glob(f"*{ext}"))
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if len(found) > 0:
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if len(found) > 1:
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logger.warning(f'More than one {ext} model has been found. The last one will be selected. It could be wrong.')
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pt_path = found[-1]
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if ext == '.safetensors':
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use_safetensors = True
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break
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if pt_path is None:
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logger.error("The model could not be loaded because its checkpoint file in .bin/.pt/.safetensors format could not be located.")
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return
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# Define the params for AutoGPTQForCausalLM.from_quantized
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params = {
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'model_basename': pt_path.stem,
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'device': "cuda:0" if not shared.args.cpu else "cpu",
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'use_triton': shared.args.triton,
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'use_safetensors': use_safetensors,
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'trust_remote_code': shared.args.trust_remote_code,
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'max_memory': get_max_memory_dict()
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}
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logger.warning(f"The AutoGPTQ params are: {params}")
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model = AutoGPTQForCausalLM.from_quantized(path_to_model, **params)
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return model
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