Instructions to use CMU-AIR2/math-deepseek-LORA-ArithHard with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use CMU-AIR2/math-deepseek-LORA-ArithHard with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-coder-1.3b-instruct") model = PeftModel.from_pretrained(base_model, "CMU-AIR2/math-deepseek-LORA-ArithHard") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 178f6e55fe45422f173e3fbc9c8462e86529a9f2e2819d132dfad7c0d5503ea4
- Size of remote file:
- 240 MB
- SHA256:
- bac2bf27f76ba10b8bb7d0aea6171dd39cb800cb897cebf7d6a638cfd591dce7
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