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numind
/
NuExtract3-FP8

Image-to-Text
Transformers
Safetensors
qwen3_5
image-text-to-text
vision-language
vlm
document-understanding
structured-extraction
information-extraction
ocr
document-to-markdown
markdown
rag
reasoning
multilingual
conversational
compressed-tensors
Model card Files Files and versions
xet
Community

Instructions to use numind/NuExtract3-FP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use numind/NuExtract3-FP8 with Transformers:

    # Use a pipeline as a high-level helper
    # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5.
    # You must load the model directly (see below) or downgrade to v4.x with:
    # 'pip install "transformers<5.0.0'
    from transformers import pipeline
    
    pipe = pipeline("image-to-text", model="numind/NuExtract3-FP8")
    messages = [
        {
            "role": "user",
            "content": [
                {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
                {"type": "text", "text": "What animal is on the candy?"}
            ]
        },
    ]
    pipe(text=messages)
    # Load model directly
    from transformers import AutoProcessor, AutoModelForImageTextToText
    
    processor = AutoProcessor.from_pretrained("numind/NuExtract3-FP8")
    model = AutoModelForImageTextToText.from_pretrained("numind/NuExtract3-FP8")
    messages = [
        {
            "role": "user",
            "content": [
                {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
                {"type": "text", "text": "What animal is on the candy?"}
            ]
        },
    ]
    inputs = processor.apply_chat_template(
    	messages,
    	add_generation_prompt=True,
    	tokenize=True,
    	return_dict=True,
    	return_tensors="pt",
    ).to(model.device)
    
    outputs = model.generate(**inputs, max_new_tokens=40)
    print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))
  • Notebooks
  • Google Colab
  • Kaggle
NuExtract3-FP8
6.54 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
SorenDreano's picture
SorenDreano
Upload folder using huggingface_hub
c2983be verified 5 days ago
  • .gitattributes
    1.57 kB
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  • chat_template.jinja
    6.75 kB
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  • config.json
    16.4 kB
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  • generation_config.json
    115 Bytes
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  • model-00001-of-00002.safetensors
    6 GB
    xet
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  • model-00002-of-00002.safetensors
    524 MB
    xet
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  • model.safetensors.index.json
    93.4 kB
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  • processor_config.json
    1.3 kB
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  • recipe.yaml
    533 Bytes
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  • tokenizer.json
    20 MB
    xet
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  • tokenizer_config.json
    1.17 kB
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