Instructions to use LossTick/clip_vision with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- OpenCLIP
How to use LossTick/clip_vision with OpenCLIP:
import open_clip model, preprocess_train, preprocess_val = open_clip.create_model_and_transforms('hf-hub:LossTick/clip_vision') tokenizer = open_clip.get_tokenizer('hf-hub:LossTick/clip_vision') - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from LossTick/clip_vision: direct link, hf CLI and curl.
- Browser
- Download file 1.71 GB
-
https://huggingface.co/LossTick/clip_vision/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://LossTick/clip_vision/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/LossTick/clip_vision/resolve/main/pytorch_model.bin
1.71 GB
- Xet hash:
- 1cc42f6dca295521183e48a523369c7b44aa54a8386600b7b9b5b0bb3fd99ccc
- Size of remote file:
- 1.71 GB
- SHA256:
- f1a17cdbe0f36fec524f5cafb1c261ea3bbbc13e346e0f74fc9eb0460dedd0d3
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