Instructions to use bczhou/TinyLLaVA-3.1B-SigLIP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bczhou/TinyLLaVA-3.1B-SigLIP with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("bczhou/TinyLLaVA-3.1B-SigLIP", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 788903bf0a25652455c3d327b0e9d012163b5c62d4230ce5059b8bc2551c0f66
- Size of remote file:
- 796 MB
- SHA256:
- fa9f7822a7b4dc4d1af3587945a034df8a55286f2d57c5c62e35c9a4c142cbec
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