Instructions to use ScalableMath/Lean-CoT-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ScalableMath/Lean-CoT-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ScalableMath/Lean-CoT-base", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ScalableMath/Lean-CoT-base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download generation_config.json from ScalableMath/Lean-CoT-base: direct link, hf CLI and curl.
- Browser
- Download file 132 Bytes
-
https://huggingface.co/ScalableMath/Lean-CoT-base/resolve/main/generation_config.json
- Command line
-
hf download hf://ScalableMath/Lean-CoT-base/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/ScalableMath/Lean-CoT-base/resolve/main/generation_config.json
132 Bytes
| { | |
| "_from_model_config": true, | |
| "bos_token_id": 1, | |
| "eos_token_id": 2, | |
| "pad_token_id": 2, | |
| "transformers_version": "4.39.3" | |
| } | |