Instructions to use CMU-AIR2/math-llama3-arith2k-mwp2k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use CMU-AIR2/math-llama3-arith2k-mwp2k with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3-8B") model = PeftModel.from_pretrained(base_model, "CMU-AIR2/math-llama3-arith2k-mwp2k") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3249c9839be1076c4d6cdf61f470f0444d485f17996f000b18beeb4e6625ab0f
- Size of remote file:
- 1.34 GB
- SHA256:
- 403ee225c825f429aa5199b73ecc3a0a7efeefb328504921c88592ff4d607768
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