Instructions to use CLASS-MATE/Mistral with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use CLASS-MATE/Mistral with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.1") model = PeftModel.from_pretrained(base_model, "CLASS-MATE/Mistral") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d65e896c04a8ae0b48b6e7a496d7f4123af07eae0a1e444d4b49bc9c02a24fe9
- Size of remote file:
- 109 MB
- SHA256:
- 6e023d90885eda29a96bfe39c0a02811ac84e7b3ecc9eabb236dc017b6ed3d3c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.