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Runtime error
| import torch | |
| from peft import PeftModel | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| from optimum.bettertransformer import BetterTransformer | |
| def load_model( | |
| base, | |
| finetuned, | |
| mode_cpu, | |
| mode_mps, | |
| mode_full_gpu, | |
| mode_8bit, | |
| mode_4bit, | |
| force_download_ckpt | |
| ): | |
| tokenizer = AutoTokenizer.from_pretrained(base) | |
| if mode_cpu: | |
| print("cpu mode") | |
| model = AutoModelForCausalLM.from_pretrained( | |
| base, | |
| device_map={"": "cpu"}, | |
| use_safetensors=False | |
| ) | |
| if finetuned is not None and \ | |
| finetuned != "" and \ | |
| finetuned != "N/A": | |
| model = PeftModel.from_pretrained( | |
| model, | |
| finetuned, | |
| device_map={"": "cpu"} | |
| # force_download=force_download_ckpt, | |
| ) | |
| else: | |
| model = BetterTransformer.transform(model) | |
| elif mode_mps: | |
| print("mps mode") | |
| model = AutoModelForCausalLM.from_pretrained( | |
| base, | |
| device_map={"": "mps"}, | |
| torch_dtype=torch.float16, | |
| use_safetensors=False | |
| ) | |
| if finetuned is not None and \ | |
| finetuned != "" and \ | |
| finetuned != "N/A": | |
| model = PeftModel.from_pretrained( | |
| model, | |
| finetuned, | |
| torch_dtype=torch.float16, | |
| device_map={"": "mps"} | |
| # force_download=force_download_ckpt, | |
| ) | |
| else: | |
| model = BetterTransformer.transform(model) | |
| else: | |
| print("gpu mode") | |
| print(f"8bit = {mode_8bit}, 4bit = {mode_4bit}") | |
| model = AutoModelForCausalLM.from_pretrained( | |
| base, | |
| load_in_8bit=mode_8bit, | |
| load_in_4bit=mode_4bit, | |
| device_map="auto", | |
| use_safetensors=False | |
| ) | |
| if not mode_8bit and not mode_4bit: | |
| model.half() | |
| if finetuned is not None and \ | |
| finetuned != "" and \ | |
| finetuned != "N/A": | |
| model = PeftModel.from_pretrained( | |
| model, | |
| finetuned, | |
| # force_download=force_download_ckpt, | |
| ) | |
| else: | |
| model = BetterTransformer.transform(model) | |
| return model, tokenizer |