model-metadata/code_python_files

1# /// script2# requires-python = ">=3.12"3# dependencies = [4#     "numpy",5#     "einops",6#     "pandas",7#     "protobuf",8#     "torch",9#     "torchvision",10#     "transformers",11#     "timm",12#     "diffusers",13#     "sentence-transformers",14#     "accelerate",15#     "peft",16#     "slack-sdk",17# ]18# ///19 20try:21    # Load model directly22    from transformers import AutoProcessor, AutoModelForImageTextToText23    24    processor = AutoProcessor.from_pretrained("LiquidAI/LFM2-VL-3B")25    model = AutoModelForImageTextToText.from_pretrained("LiquidAI/LFM2-VL-3B")26    messages = [27        {28            "role": "user",29            "content": [30                {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},31                {"type": "text", "text": "What animal is on the candy?"}32            ]33        },34    ]35    inputs = processor.apply_chat_template(36    	messages,37    	add_generation_prompt=True,38    	tokenize=True,39    	return_dict=True,40    	return_tensors="pt",41    ).to(model.device)42    43    outputs = model.generate(**inputs, max_new_tokens=40)44    print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))45    with open('LiquidAI_LFM2-VL-3B_1.txt', 'w', encoding='utf-8') as f:46        f.write('Everything was good in LiquidAI_LFM2-VL-3B_1.txt')47except Exception as e:48    import os49    from slack_sdk import WebClient50    client = WebClient(token=os.environ['SLACK_TOKEN'])51    client.chat_postMessage(52        channel='#hub-model-metadata-snippets-sprint',53        text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/LiquidAI_LFM2-VL-3B_1.txt|LiquidAI_LFM2-VL-3B_1.txt>',54    )55 56    with open('LiquidAI_LFM2-VL-3B_1.txt', 'a', encoding='utf-8') as f:57        import traceback58        f.write('''```CODE: 59# Load model directly60from transformers import AutoProcessor, AutoModelForImageTextToText61 62processor = AutoProcessor.from_pretrained("LiquidAI/LFM2-VL-3B")63model = AutoModelForImageTextToText.from_pretrained("LiquidAI/LFM2-VL-3B")64messages = [65    {66        "role": "user",67        "content": [68            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},69            {"type": "text", "text": "What animal is on the candy?"}70        ]71    },72]73inputs = processor.apply_chat_template(74	messages,75	add_generation_prompt=True,76	tokenize=True,77	return_dict=True,78	return_tensors="pt",79).to(model.device)80 81outputs = model.generate(**inputs, max_new_tokens=40)82print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))83```84 85ERROR: 86''')87        traceback.print_exc(file=f)88    89finally:90    from huggingface_hub import upload_file91    upload_file(92        path_or_fileobj='LiquidAI_LFM2-VL-3B_1.txt',93        repo_id='model-metadata/code_execution_files',94        path_in_repo='LiquidAI_LFM2-VL-3B_1.txt',95        repo_type='dataset',96    )97