| from transformers import ( | |
| AutoModelForCausalLM, | |
| AutoTokenizer, | |
| AutoTokenizer, | |
| ) | |
| import torch | |
| d_map = {"": torch.cuda.current_device()} if torch.cuda.is_available() else None | |
| merged_model_path = "outputs/merged" # Path to the combined weights | |
| repo_name = "Financial_Analyst" # HuggingFace repo name | |
| model = AutoModelForCausalLM.from_pretrained( | |
| merged_model_path, | |
| ignore_mismatched_sizes=True, | |
| from_tf=True, | |
| trust_remote_code=True, | |
| device_map=d_map, | |
| torch_dtype=torch.float16, | |
| ).eval() | |
| tokenizer = AutoTokenizer.from_pretrained(merged_model_path) | |
| model.push_to_hub(repo_name, token=hf_token) | |
| tokenizer.push_to_hub(repo_name, token=hf_token) | |