Instructions to use sectionme/granite-clm-g2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sectionme/granite-clm-g2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("sectionme/granite-clm-g2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from sectionme/granite-clm-g2: direct link, hf CLI and curl.
- Browser
- Download file 25.3 MB
-
https://huggingface.co/sectionme/granite-clm-g2/resolve/main/tokenizer.json
- Command line
-
hf download hf://sectionme/granite-clm-g2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/sectionme/granite-clm-g2/resolve/main/tokenizer.json
25.3 MB
- Xet hash:
- a07bbc0faa4bf0e353bf525b99d87019f100b08340e09c29ee37325ee57671dd
- Size of remote file:
- 25.3 MB
- SHA256:
- a5a0e0fd1ee629250af8923df45ffe17e02a900e915507af3bac7def282a4b99
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