Instructions to use viraad/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use viraad/results with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("ybelkada/falcon-7b-sharded-bf16") model = PeftModel.from_pretrained(base_model, "viraad/results") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 837144d797970254a3c7251dbbfaa9deeaab9b1d183ec7c2068964199a186aa4
- Size of remote file:
- 4.73 kB
- SHA256:
- 77cfc1f5e9dd6b3d64c475ddea8e1372690b2157e917874d7a871c9be23f43e4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.