Instructions to use UCSC-VLAA/openvision-vit-base-patch16-384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- OpenCLIP
How to use UCSC-VLAA/openvision-vit-base-patch16-384 with OpenCLIP:
import open_clip model, preprocess_train, preprocess_val = open_clip.create_model_and_transforms('hf-hub:UCSC-VLAA/openvision-vit-base-patch16-384') tokenizer = open_clip.get_tokenizer('hf-hub:UCSC-VLAA/openvision-vit-base-patch16-384') - Notebooks
- Google Colab
- Kaggle
Add model card
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by nielsr HF Staff - opened
README.md
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---
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license: apache-2.0
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library_name: open_clip
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pipeline_tag: image-feature-extraction
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---
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# OpenVision
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This repository contains the model for the OpenVision encoder described in [OpenVision: A Fully-Open, Cost-Effective Family of Advanced Vision Encoders for Multimodal Learning](https://huggingface.co/papers/2505.04601).
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The models provide image features and are suitable for use in multimodal systems.
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Project page: https://ucsc-vlaa.github.io/OpenVision
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Code: https://github.com/UCSC-VLAA/OpenVision.
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