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:
- 562d949aa984e2e38066be1cd6cdf7010e619ed803f42915e4ceccc6b5c44051
- Size of remote file:
- 25.7 MB
- SHA256:
- fd43ce7f1c71d5b69fac9a4970f915334fef2f826017655393274c6480a0a552
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.