Instructions to use CMU-AIR2/math-llama3-instruct-MWP2K with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use CMU-AIR2/math-llama3-instruct-MWP2K with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3-8B-Instruct") model = PeftModel.from_pretrained(base_model, "CMU-AIR2/math-llama3-instruct-MWP2K") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 752b9a25131cc3a7249ef40072da15705f7cb0d9be76bee20b3af3ee7ace570d
- Size of remote file:
- 4.92 kB
- SHA256:
- cc1b2f9b0809cc2aaa3b6943d440fdd51526faedf064787ab43eb96f13072a96
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.