Instructions to use bleugreen/mistral_backprompt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use bleugreen/mistral_backprompt 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, "bleugreen/mistral_backprompt") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from bleugreen/mistral_backprompt: direct link, hf CLI and curl.
- Browser
- Download file 218 MB
-
https://huggingface.co/bleugreen/mistral_backprompt/resolve/main/adapter_model.bin
- Command line
-
hf download hf://bleugreen/mistral_backprompt/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/bleugreen/mistral_backprompt/resolve/main/adapter_model.bin
218 MB
- Xet hash:
- 7f0187bf62c691bdb7216ec67b9539df4452ed63692b94f37d7e2f167a1b4aa5
- Size of remote file:
- 218 MB
- SHA256:
- 57c0e1b9d4c7e45673fc9dba57599ffa38dc6952cb96bdc5f6b88b5589bbebc1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.