Visual Document Retrieval
Transformers
Safetensors
ColPali
multilingual
qwen3_vl_nemotron_embed
feature-extraction
text
image
vidore
multimodal-embedding
multilingual-embedding
Text-to-Visual Document (T→VD) retrieval
custom_code
Instructions to use nvidia/nemotron-colembed-vl-4b-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/nemotron-colembed-vl-4b-v2 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nvidia/nemotron-colembed-vl-4b-v2", trust_remote_code=True, device_map="auto") - ColPali
How to use nvidia/nemotron-colembed-vl-4b-v2 with ColPali:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -35,7 +35,7 @@ The **nvidia/nemotron-colembed-vl-4b-v2** is a state-of-the-art late interaction
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* 🌍 **Enhanced Synthetic Data:** We significantly enriched our training mixture with diverse multilingual synthetic data, improving semantic alignment across languages and complex document types.
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This model is for non-commercial/research use only.
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### License/Terms of Use
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The use of this model is governed by the [Creative Commons Attribution-NonCommercial 4.0 license](https://creativecommons.org/licenses/by-nc/4.0/deed.en), and the use of the post-processing scripts are licensed under [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0.txt). Additional Information: Built with Qwen3-VL which is released under [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0.txt).
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* 🌍 **Enhanced Synthetic Data:** We significantly enriched our training mixture with diverse multilingual synthetic data, improving semantic alignment across languages and complex document types.
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This model is for non-commercial/research use only.
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See the Nemotron ColEmbed v2 [paper](https://arxiv.org/abs/2602.03992) for more details about its architecture, training and results.
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### License/Terms of Use
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The use of this model is governed by the [Creative Commons Attribution-NonCommercial 4.0 license](https://creativecommons.org/licenses/by-nc/4.0/deed.en), and the use of the post-processing scripts are licensed under [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0.txt). Additional Information: Built with Qwen3-VL which is released under [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0.txt).
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