Instructions to use Saliltrehan7/mistral-finetuned-samsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Saliltrehan7/mistral-finetuned-samsum with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("TheBloke/Mistral-7B-Instruct-v0.1-GPTQ") model = PeftModel.from_pretrained(base_model, "Saliltrehan7/mistral-finetuned-samsum") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 92299817ec6dfd540698854180f2fd9fed5d14321a29e0d990e4a9a5af075c09
- Size of remote file:
- 27.3 MB
- SHA256:
- 1381b20167d3b563534c76eb3a89a9e3d9ad10b853b401324a97641da4d4e01d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.