Instructions to use llm-jp/llm-jp-clip-vit-base-patch16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- OpenCLIP
How to use llm-jp/llm-jp-clip-vit-base-patch16 with OpenCLIP:
import open_clip model, preprocess_train, preprocess_val = open_clip.create_model_and_transforms('hf-hub:llm-jp/llm-jp-clip-vit-base-patch16') tokenizer = open_clip.get_tokenizer('hf-hub:llm-jp/llm-jp-clip-vit-base-patch16') - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aa7ff017d1c232135452afcf329423f97bd6994020d0307cb9c08d100931fb1d
- Size of remote file:
- 996 MB
- SHA256:
- abc3cb2461ef5c940544de5da49dcedf01f4545afb27fc16bc3520d556be9b55
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