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", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 19e04166fb55646454fd8c663b827d270e7884f56e9f756157bf26a19d7d82b8
- Size of remote file:
- 796 MB
- SHA256:
- 6d1ec2f27a931c342276c03715bd2e0b4494888a1309c3e74eaa94dc0a89ae7a
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