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:
- f0592eea6ebd416bec9fad6f64d567d45e34150231d05d88dd09cc3cd5e3ddbf
- Size of remote file:
- 4.92 kB
- SHA256:
- 7efa3795ddd3cb44c7e9ba546c0eb57003af5aca212994866fdc9f1474c1f0bc
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