Text Generation
PEFT
PyTorch
Safetensors
mistral
Generated from Trainer
conversational
4-bit precision
bitsandbytes
Instructions to use HeroMask/Meddi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use HeroMask/Meddi 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, "HeroMask/Meddi") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0c6680a9d562c194d63c57a8c42a126d72f5c0731ce0231baecfe02d1490ddd7
- Size of remote file:
- 1.05 MB
- SHA256:
- cce654fbb2a5be5dae643a4545c346a5350c1ccc79ce0ea14198a1920823dfd4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.