| import torch | |
| import transformers | |
| from transformers import AutoModelForCausalLM | |
| from lm_quant_toolkit.adapter.common import get_model_storage_size | |
| from lm_quant_toolkit.utils.hub import get_hf_model_storge_base_dir | |
| def create_fp16_model(model_id, quant_config, config_id, load_quantized, save_dir): | |
| model_file_size = 0 | |
| model = AutoModelForCausalLM.from_pretrained( | |
| model_id, device_map="auto", torch_dtype=torch.float16 | |
| ) | |
| tokenizer = transformers.AutoTokenizer.from_pretrained(model_id) | |
| base_dir = get_hf_model_storge_base_dir(model_id) | |
| model_file_size = get_model_storage_size(base_dir) | |
| return model, tokenizer, False, model_file_size | |