Instructions to use czagnos/challenge_adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use czagnos/challenge_adapter with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("czagnos/challenge_adapter", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from czagnos/challenge_adapter: direct link, hf CLI and curl.
- Browser
- Download file 33.4 MB
-
https://huggingface.co/czagnos/challenge_adapter/resolve/main/tokenizer.json
- Command line
-
hf download hf://czagnos/challenge_adapter/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/czagnos/challenge_adapter/resolve/main/tokenizer.json
33.4 MB
- Xet hash:
- 67d1b1bbda180fc0d3b28574fe6ee52aaf13433a87ed7d97fd2f77be17fa8f85
- Size of remote file:
- 33.4 MB
- SHA256:
- 34e3f436416642ff2b4cba0602975a87bd8766c9f3b1851dde39479073bafd08
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