Instructions to use Prahaladha/math-checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Prahaladha/math-checkpoints with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Prahaladha/math-checkpoints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download final/tokenizer.json from Prahaladha/math-checkpoints: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/Prahaladha/math-checkpoints/resolve/main/final/tokenizer.json
- Command line
-
hf download hf://Prahaladha/math-checkpoints/final/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Prahaladha/math-checkpoints/resolve/main/final/tokenizer.json
11.4 MB
- Xet hash:
- dffb4edddda5c45adca8b8fdec0266bad247eed0d8668fc6acf6f089c28e7761
- Size of remote file:
- 11.4 MB
- SHA256:
- 783271f25c4345398bf586ffdd649e4a17f2e2d607141b7cf7864ca8aa17af7e
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