Instructions to use shastraai/Shastra-Mistral-Math-SFT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use shastraai/Shastra-Mistral-Math-SFT with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("TheBloke/Mistral-7B-v0.1-GPTQ") model = PeftModel.from_pretrained(base_model, "shastraai/Shastra-Mistral-Math-SFT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 113353b600a1efc7e5db556cd004cae148fcdd7c94ce2cfd667c5bf5fc6cb11e
- Size of remote file:
- 5.56 kB
- SHA256:
- 8237aaa73504ced79b018b332986f5b86521d69fdaf8008c3ef2510cc617ee5e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.