add gptq option for ppl test (#11921)
* feat:add gptq for ppl * fix: add an empty line * fix: add an empty line * fix: remove an empty line * Resolve comments * Resolve comments * Resolve comments
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1 changed files with 15 additions and 3 deletions
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@ -38,12 +38,24 @@ args = parser.parse_args()
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if args.precision == "fp16": # ipex fp16
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if args.precision == "fp16": # ipex fp16
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from transformers import AutoModelForCausalLM
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from transformers import AutoModelForCausalLM
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model = AutoModelForCausalLM.from_pretrained(args.model_path, use_cache=args.use_cache, trust_remote_code=True)
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model = AutoModelForCausalLM.from_pretrained(args.model_path,
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use_cache=args.use_cache,
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trust_remote_code=True)
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model = model.half()
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model = model.half()
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elif 'gptq' in args.model_path.lower(): # ipex-llm gptq
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from ipex_llm.transformers import AutoModelForCausalLM
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model = AutoModelForCausalLM.from_pretrained(args.model_path,
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load_in_4bit=True,
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torch_dtype=torch.float,
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use_cache=args.use_cache,
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trust_remote_code=True)
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else: # ipex-llm
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else: # ipex-llm
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from ipex_llm.transformers import AutoModelForCausalLM
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from ipex_llm.transformers import AutoModelForCausalLM
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model = AutoModelForCausalLM.from_pretrained(args.model_path, load_in_low_bit=args.precision,
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model = AutoModelForCausalLM.from_pretrained(args.model_path,
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use_cache=args.use_cache, trust_remote_code=True, mixed_precision= args.mixed_precision)
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load_in_low_bit=args.precision,
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use_cache=args.use_cache,
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trust_remote_code=True,
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mixed_precision=args.mixed_precision)
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model = model.half()
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model = model.half()
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model = model.to(args.device)
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model = model.to(args.device)
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model = model.eval()
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model = model.eval()
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