Instructions to use gvij/eng-hing-a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use gvij/eng-hing-a with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-2-2b-it") model = PeftModel.from_pretrained(base_model, "gvij/eng-hing-a") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 392714288e8b067abf0fdaf0e1b1fa7eb0d57d227783593e404cf039cec4b93e
- Size of remote file:
- 5.24 kB
- SHA256:
- d5811affd71702e613455e43b22103be390789e587149ccf0932974c47178530
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.