Instructions to use Tesslate/Gradience-RL-Math with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tesslate/Gradience-RL-Math with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Tesslate/Gradience-RL-Math", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download final_checkpoint/tokenizer.json from Tesslate/Gradience-RL-Math: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/Tesslate/Gradience-RL-Math/resolve/main/final_checkpoint/tokenizer.json
- Command line
-
hf download hf://Tesslate/Gradience-RL-Math/final_checkpoint/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Tesslate/Gradience-RL-Math/resolve/main/final_checkpoint/tokenizer.json
11.4 MB
- Xet hash:
- b1386d70854cfefd60e569ee033399ce5db5f1e9b001eabb74e0ab417a39a1a9
- Size of remote file:
- 11.4 MB
- SHA256:
- 5eee858c5123a4279c3e1f7b81247343f356ac767940b2692a928ad929543214
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