Instructions to use odoom/nixpkgs-security-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use odoom/nixpkgs-security-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2") model = PeftModel.from_pretrained(base_model, "odoom/nixpkgs-security-lora") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from odoom/nixpkgs-security-lora: direct link, hf CLI and curl.
- Browser
- Download file 5.65 kB
-
https://huggingface.co/odoom/nixpkgs-security-lora/resolve/main/training_args.bin
- Command line
-
hf download hf://odoom/nixpkgs-security-lora/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/odoom/nixpkgs-security-lora/resolve/main/training_args.bin
5.65 kB
- Xet hash:
- d1eab3305851cc17ece764aa1c83846d3207660b35bdfdfa5a018f1294cc7724
- Size of remote file:
- 5.65 kB
- SHA256:
- 13b53f9087af6406754f9d4a944b842846aaebb983e7344dbff137c8f3f21285
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.