Upload CohereLabs_command-a-vision-07-2025_1.py with huggingface_hub
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CohereLabs_command-a-vision-07-2025_1.py
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# /// script
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# requires-python = ">=3.12"
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# dependencies = [
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# "transformers",
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# "torch",
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# ]
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# ///
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try:
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# Load model directly
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from transformers import AutoProcessor, AutoModelForImageTextToText
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processor = AutoProcessor.from_pretrained("CohereLabs/command-a-vision-07-2025")
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model = AutoModelForImageTextToText.from_pretrained("CohereLabs/command-a-vision-07-2025")
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messages = [
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{
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"role": "user",
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"content": [
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{"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
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{"type": "text", "text": "What animal is on the candy?"}
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]
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},
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]
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inputs = processor.apply_chat_template(
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messages,
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add_generation_prompt=True,
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tokenize=True,
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return_dict=True,
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return_tensors="pt",
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).to(model.device)
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outputs = model.generate(**inputs, max_new_tokens=40)
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print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))
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with open('CohereLabs_command-a-vision-07-2025_1.txt', 'w') as f:
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f.write('Everything was good in CohereLabs_command-a-vision-07-2025_1.txt')
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except Exception as e:
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with open('CohereLabs_command-a-vision-07-2025_1.txt', 'w') as f:
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import traceback
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traceback.print_exc(file=f)
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finally:
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from huggingface_hub import upload_file
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upload_file(
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path_or_fileobj='CohereLabs_command-a-vision-07-2025_1.txt',
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repo_id='model-metadata/custom_code_execution_files',
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path_in_repo='CohereLabs_command-a-vision-07-2025_1.txt',
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repo_type='dataset',
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)
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