(args)
| 48 | |
| 49 | # load model and tokenizer |
| 50 | def load(args): |
| 51 | |
| 52 | # define the model |
| 53 | misc.init_distributed_mode(args) |
| 54 | fs_init.initialize_model_parallel(args.model_parallel_size) |
| 55 | model = MetaModel(args.llama_type, args.llama_config, args.tokenizer_path, with_visual=True) |
| 56 | print(f"load pretrained from {args.pretrained_path}") |
| 57 | load_tensor_parallel_model_list(model, args.pretrained_path) |
| 58 | |
| 59 | if args.quant: |
| 60 | print("Quantizing model to 4bit!") |
| 61 | |
| 62 | from transformers.utils.quantization_config import BitsAndBytesConfig |
| 63 | quantization_config = BitsAndBytesConfig.from_dict( |
| 64 | config_dict={ |
| 65 | "load_in_8bit": False, |
| 66 | "load_in_4bit": True, |
| 67 | "bnb_4bit_quant_type": "nf4", |
| 68 | }, |
| 69 | return_unused_kwargs=False, |
| 70 | ) |
| 71 | quantize(model, quantization_config) |
| 72 | |
| 73 | #print("Model = %s" % str(model)) |
| 74 | model.bfloat16().cuda() |
| 75 | return model |
| 76 | |
| 77 | def entry_point( |
| 78 | sample_file: str, |
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