Image-to-Text
Transformers
Safetensors
image-text-to-text
qwen3_5
vision-language
vlm
document-understanding
structured-extraction
information-extraction
ocr
document-to-markdown
markdown
rag
reasoning
multilingual
conversational
Instructions to use numind/NuExtract3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use numind/NuExtract3 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") 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 AutoModel model = AutoModel.from_pretrained("numind/NuExtract3", dtype="auto") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 816b228df9795f964e90a0da607851206e29ff3a0330549b6df5fa5f2be3c82b
- Size of remote file:
- 161 kB
- SHA256:
- 733f46ad4c82186626df2db2927f0eadd5d7089ba98cec4aabb9281a7b114285
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