Instructions to use 7fno/dersat-gemma-optional with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 7fno/dersat-gemma-optional with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("7fno/dersat-gemma-optional", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from 7fno/dersat-gemma-optional: direct link, hf CLI and curl.
- Browser
- Download file 17.5 MB
-
https://huggingface.co/7fno/dersat-gemma-optional/resolve/main/tokenizer.json
- Command line
-
hf download hf://7fno/dersat-gemma-optional/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/7fno/dersat-gemma-optional/resolve/main/tokenizer.json
17.5 MB
- Xet hash:
- 2d8fb0bb1788175e4329f8ac87cec7916e2bfc9d9daf9f4c53f0efa0763dc09f
- Size of remote file:
- 17.5 MB
- SHA256:
- 4ecf26e94dffb08d544f582c32358f4870097efa8629a13208c020152f8d06a3
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