HuggingFaceTB_SmolLM3-3B_6.py

# /// script
# requires-python = ">=3.12"
# dependencies = [
#     "torch",
#     "torchvision",
#     "transformers",
#     "diffusers",
#     "sentence-transformers",
#     "accelerate",
#     "peft",
#     "slack-sdk",
# ]
# ///

try:
    tools = [
        {
            "name": "get_weather",
            "description": "Get the weather in a city",
            "parameters": {"type": "object", "properties": {"city": {"type": "string", "description": "The city to get the weather for"}}}}
    ]
    
    messages = [
        {
            "role": "user",
            "content": "Hello! How is the weather today in Copenhagen?"
        }
    ]
    
    inputs = tokenizer.apply_chat_template(
        messages,
        enable_thinking=False, # True works as well, your choice!
        xml_tools=tools,
        add_generation_prompt=True,
        tokenize=True,
        return_tensors="pt"
    ).to(model.device)
    
    outputs = model.generate(inputs)
    print(tokenizer.decode(outputs[0]))
    with open('HuggingFaceTB_SmolLM3-3B_6.txt', 'w', encoding='utf-8') as f:
        f.write('Everything was good in HuggingFaceTB_SmolLM3-3B_6.txt')
except Exception as e:
    import os
    from slack_sdk import WebClient
    client = WebClient(token=os.environ['SLACK_TOKEN'])
    client.chat_postMessage(
        channel='#hub-model-metadata-snippets-sprint',
        text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/HuggingFaceTB_SmolLM3-3B_6.txt|HuggingFaceTB_SmolLM3-3B_6.txt>',
    )

    with open('HuggingFaceTB_SmolLM3-3B_6.txt', 'a', encoding='utf-8') as f:
        import traceback
        f.write('''```CODE: 
tools = [
    {
        "name": "get_weather",
        "description": "Get the weather in a city",
        "parameters": {"type": "object", "properties": {"city": {"type": "string", "description": "The city to get the weather for"}}}}
]

messages = [
    {
        "role": "user",
        "content": "Hello! How is the weather today in Copenhagen?"
    }
]

inputs = tokenizer.apply_chat_template(
    messages,
    enable_thinking=False, # True works as well, your choice!
    xml_tools=tools,
    add_generation_prompt=True,
    tokenize=True,
    return_tensors="pt"
).to(model.device)

outputs = model.generate(inputs)
print(tokenizer.decode(outputs[0]))
```

ERROR: 
''')
        traceback.print_exc(file=f)
    
finally:
    from huggingface_hub import upload_file
    upload_file(
        path_or_fileobj='HuggingFaceTB_SmolLM3-3B_6.txt',
        repo_id='model-metadata/code_execution_files',
        path_in_repo='HuggingFaceTB_SmolLM3-3B_6.txt',
        repo_type='dataset',
    )