Instructions to use perelloliver/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use perelloliver/results with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/Phi-3-mini-128k-instruct") model = PeftModel.from_pretrained(base_model, "perelloliver/results") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from perelloliver/results: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/perelloliver/results/resolve/main/training_args.bin
- Command line
-
hf download hf://perelloliver/results/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/perelloliver/results/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 84a8970e0d83e96134ba9f59a8167b79dfe309f9ec306676651516447751a840
- Size of remote file:
- 4.92 kB
- SHA256:
- e47f997e0813dc6ce62a0187261d8da12b77974d3196b1478cbc72bcc96d4c99
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.