Instructions to use ksjpswaroop/math_savvy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ksjpswaroop/math_savvy with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ksjpswaroop/math_savvy", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ksjpswaroop/math_savvy: direct link, hf CLI and curl.
- Browser
- Download file 1.8 MB
-
https://huggingface.co/ksjpswaroop/math_savvy/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://ksjpswaroop/math_savvy@refs/pr/1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ksjpswaroop/math_savvy/resolve/refs%2Fpr%2F1/tokenizer.json
1.8 MB
- Xet hash:
- c42c914821885fa3012a8214151a1721216cb2350828199736001effd9aaa0da
- Size of remote file:
- 1.8 MB
- SHA256:
- fc4f0bd70b3709312d9d1d9e5ba674794b6bc5abc17429897a540f93882f25fc
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