Instructions to use ancerlop/Mistral with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ancerlop/Mistral with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("bn22/Mistral-7B-Instruct-v0.1-sharded") model = PeftModel.from_pretrained(base_model, "ancerlop/Mistral") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9c7b836ffa513bb169e8cce8f308a629f329b221a76cd1fc74c1f134cb7da601
- Size of remote file:
- 27.3 MB
- SHA256:
- bcbff33e5c4dcbf59970d9e687b91b6459688e91f55a9fb410a72b06384c0d68
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.