Instructions to use ckpt/ModelScope with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- OpenCLIP
How to use ckpt/ModelScope with OpenCLIP:
import open_clip model, preprocess_train, preprocess_val = open_clip.create_model_and_transforms('hf-hub:ckpt/ModelScope') tokenizer = open_clip.get_tokenizer('hf-hub:ckpt/ModelScope') - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a5fb4af5b31b8ab5448cd86d55ff12826844061f321c5bbbcbedfd77103bd943
- Size of remote file:
- 1.97 GB
- SHA256:
- 73c32c62eebf1112b0693ff9e3ecfa0573ba02cd279420ea4da4af1cbfb39e3b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.