Upload HuggingFaceTB_SmolLM3-3B_4.py with huggingface_hub

HuggingFaceTB_SmolLM3-3B_4.py

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+# /// script
+# requires-python = ">=3.12"
+# dependencies = [
+#     "torch",
+#     "torchvision",
+#     "transformers",
+#     "diffusers",
+#     "sentence-transformers",
+#     "accelerate",
+#     "peft",
+#     "slack-sdk",
+# ]
+# ///
+
+try:
+    # prepare the model input
+    prompt = "Give me a brief explanation of gravity in simple terms."
+    messages_think = [
+        {"role": "user", "content": prompt}
+    ]
+    
+    text = tokenizer.apply_chat_template(
+        messages_think,
+        tokenize=False,
+        add_generation_prompt=True,
+    )
+    model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
+    
+    # Generate the output
+    generated_ids = model.generate(**model_inputs, max_new_tokens=32768)
+    
+    # Get and decode the output
+    output_ids = generated_ids[0][len(model_inputs.input_ids[0]) :]
+    print(tokenizer.decode(output_ids, skip_special_tokens=True))
+    with open('HuggingFaceTB_SmolLM3-3B_4.txt', 'w', encoding='utf-8') as f:
+        f.write('Everything was good in HuggingFaceTB_SmolLM3-3B_4.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_4.txt|HuggingFaceTB_SmolLM3-3B_4.txt>',
+    )
+
+    with open('HuggingFaceTB_SmolLM3-3B_4.txt', 'a', encoding='utf-8') as f:
+        import traceback
+        f.write('''```CODE: 
+# prepare the model input
+prompt = "Give me a brief explanation of gravity in simple terms."
+messages_think = [
+    {"role": "user", "content": prompt}
+]
+
+text = tokenizer.apply_chat_template(
+    messages_think,
+    tokenize=False,
+    add_generation_prompt=True,
+)
+model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
+
+# Generate the output
+generated_ids = model.generate(**model_inputs, max_new_tokens=32768)
+
+# Get and decode the output
+output_ids = generated_ids[0][len(model_inputs.input_ids[0]) :]
+print(tokenizer.decode(output_ids, skip_special_tokens=True))
+```
+
+ERROR: 
+''')
+        traceback.print_exc(file=f)
+    
+finally:
+    from huggingface_hub import upload_file
+    upload_file(
+        path_or_fileobj='HuggingFaceTB_SmolLM3-3B_4.txt',
+        repo_id='model-metadata/code_execution_files',
+        path_in_repo='HuggingFaceTB_SmolLM3-3B_4.txt',
+        repo_type='dataset',
+    )