Text Generation
PEFT
Safetensors
French
orpo
preference-optimization
qlora
negative-result
failure-analysis
csrd
esrs
regulatory
alignment
conversational
Instructions to use CID99/Mistral-7B-ORPO-CSRD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use CID99/Mistral-7B-ORPO-CSRD with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.3") model = PeftModel.from_pretrained(base_model, "CID99/Mistral-7B-ORPO-CSRD") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from CID99/Mistral-7B-ORPO-CSRD: direct link, hf CLI and curl.
- Browser
- Download file 3.67 MB
-
https://huggingface.co/CID99/Mistral-7B-ORPO-CSRD/resolve/main/tokenizer.json
- Command line
-
hf download hf://CID99/Mistral-7B-ORPO-CSRD/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/CID99/Mistral-7B-ORPO-CSRD/resolve/main/tokenizer.json
3.67 MB
File too large to display, you can check the raw version instead.