Instructions to use CMU-AIR2/math-deepseek-lora-hard-arith with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use CMU-AIR2/math-deepseek-lora-hard-arith 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-hard-arith") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1d474ea72a6c4341c82de509f73a1a628c355fb8ced4734366260de532f04baa
- Size of remote file:
- 60.5 MB
- SHA256:
- 32384f54d47697f7a043d0ceca2c9ff94b98427cd8dd85f63ab01c8823311759
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