Instructions to use rayonlabs/instructtestdiag with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use rayonlabs/instructtestdiag with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("samoline/b7447218-27e6-491c-b3ab-ea03a5b93541") model = PeftModel.from_pretrained(base_model, "rayonlabs/instructtestdiag") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-6/optimizer.pt from rayonlabs/instructtestdiag: direct link, hf CLI and curl.
- Browser
- Download file 11.7 MB
-
https://huggingface.co/rayonlabs/instructtestdiag/resolve/main/checkpoint-6/optimizer.pt
- Command line
-
hf download hf://rayonlabs/instructtestdiag/checkpoint-6/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/rayonlabs/instructtestdiag/resolve/main/checkpoint-6/optimizer.pt
11.7 MB
- Xet hash:
- 261c9e4ee9cb53748c0275820ed7d3deb53e510c089e68959d8d84df44e22971
- Size of remote file:
- 11.7 MB
- SHA256:
- 83490f8c55ce238ffec7a95413b705534fa808c5d9353246ff841bcd3f6988c2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.