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Revert GPTQ_loader.py (accident)
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@ -14,7 +14,7 @@ import opt
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def load_quantized(model_name):
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if not shared.args.model_type:
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if not shared.args.gptq_model_type:
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# Try to determine model type from model name
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model_type = model_name.split('-')[0].lower()
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if model_type not in ('llama', 'opt'):
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@ -22,10 +22,10 @@ def load_quantized(model_name):
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"argument")
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exit()
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else:
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model_type = shared.args.model_type.lower()
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model_type = shared.args.gptq_model_type.lower()
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if model_type == 'llama':
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if not shared.args.pre_layer:
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if not shared.args.gptq_pre_layer:
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load_quant = llama.load_quant
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else:
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load_quant = llama_inference_offload.load_quant
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@ -37,15 +37,15 @@ def load_quantized(model_name):
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path_to_model = Path(f'models/{model_name}')
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if path_to_model.name.lower().startswith('llama-7b'):
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pt_model = f'llama-7b-{shared.args.wbits}bit.pt'
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pt_model = f'llama-7b-{shared.args.gptq_bits}bit.pt'
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elif path_to_model.name.lower().startswith('llama-13b'):
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pt_model = f'llama-13b-{shared.args.wbits}bit.pt'
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pt_model = f'llama-13b-{shared.args.gptq_bits}bit.pt'
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elif path_to_model.name.lower().startswith('llama-30b'):
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pt_model = f'llama-30b-{shared.args.wbits}bit.pt'
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pt_model = f'llama-30b-{shared.args.gptq_bits}bit.pt'
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elif path_to_model.name.lower().startswith('llama-65b'):
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pt_model = f'llama-65b-{shared.args.wbits}bit.pt'
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pt_model = f'llama-65b-{shared.args.gptq_bits}bit.pt'
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else:
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pt_model = f'{model_name}-{shared.args.wbits}bit.pt'
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pt_model = f'{model_name}-{shared.args.gptq_bits}bit.pt'
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# Try to find the .pt both in models/ and in the subfolder
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pt_path = None
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@ -58,10 +58,10 @@ def load_quantized(model_name):
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exit()
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# qwopqwop200's offload
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if shared.args.pre_layer:
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model = load_quant(str(path_to_model), str(pt_path), shared.args.wbits, shared.args.pre_layer)
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if shared.args.gptq_pre_layer:
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model = load_quant(str(path_to_model), str(pt_path), shared.args.gptq_bits, shared.args.gptq_pre_layer)
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else:
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model = load_quant(str(path_to_model), str(pt_path), shared.args.wbits)
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model = load_quant(str(path_to_model), str(pt_path), shared.args.gptq_bits)
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# accelerate offload (doesn't work properly)
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if shared.args.gpu_memory:
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