| # /// script | |
| # requires-python = ">=3.12" | |
| # dependencies = [ | |
| # "transformers", | |
| # "torch", | |
| # ] | |
| # /// | |
| try: | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| model_name = "HuggingFaceTB/SmolLM3-3B" | |
| device = "cuda" # for GPU usage or "cpu" for CPU usage | |
| # load the tokenizer and the model | |
| tokenizer = AutoTokenizer.from_pretrained(model_name) | |
| model = AutoModelForCausalLM.from_pretrained( | |
| model_name, | |
| ).to(device) | |
| with open('HuggingFaceTB_SmolLM3-3B_3.txt', 'w') as f: | |
| f.write('Everything was good in HuggingFaceTB_SmolLM3-3B_3.txt') | |
| except Exception as e: | |
| with open('HuggingFaceTB_SmolLM3-3B_3.txt', 'w') as f: | |
| import traceback | |
| traceback.print_exc(file=f) | |
| finally: | |
| from huggingface_hub import upload_file | |
| upload_file( | |
| path_or_fileobj='HuggingFaceTB_SmolLM3-3B_3.txt', | |
| repo_id='model-metadata/custom_code_execution_files', | |
| path_in_repo='HuggingFaceTB_SmolLM3-3B_3.txt', | |
| repo_type='dataset', | |
| ) |