Instructions to use MatanP/MISTRAL_fine_tuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use MatanP/MISTRAL_fine_tuned with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.3") model = PeftModel.from_pretrained(base_model, "MatanP/MISTRAL_fine_tuned") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from MatanP/MISTRAL_fine_tuned: direct link, hf CLI and curl.
- Browser
- Download file 5.5 kB
-
https://huggingface.co/MatanP/MISTRAL_fine_tuned/resolve/main/training_args.bin
- Command line
-
hf download hf://MatanP/MISTRAL_fine_tuned/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/MatanP/MISTRAL_fine_tuned/resolve/main/training_args.bin
5.5 kB
- Xet hash:
- 41db707fed9a9de589437db7b7fa0c38eafc4c347d1bdf6c4fecb02178a039f3
- Size of remote file:
- 5.5 kB
- SHA256:
- 86aa0bc6b8d6c97958b7824110ccad8862c88f597159635b7287a8cda7442943
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