# /// script
# requires-python = ">=3.12"
# dependencies = [
#     "numpy",
#     "einops",
#     "torch",
#     "transformers",
#     "datasets",
#     "accelerate",
#     "timm",
# ]
# ///

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',
    )