Instructions to use bczhou/TinyLLaVA-2.0B-SigLIP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bczhou/TinyLLaVA-2.0B-SigLIP with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("bczhou/TinyLLaVA-2.0B-SigLIP", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 38bba74318743cb74067ff4d23e4343381bf9dd2f22baa11b51cbf408c023ef1
- Size of remote file:
- 796 MB
- SHA256:
- f3afdfd2421018cc8a7e4f5b83b9648fb4502a1f1a43bcc3718af3dda15de773
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