Instructions to use Tung177/gemma-2-2b-4bite2r256bs16-vi-sentence-simplification-adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Tung177/gemma-2-2b-4bite2r256bs16-vi-sentence-simplification-adapter with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-2-9b") model = PeftModel.from_pretrained(base_model, "Tung177/gemma-2-2b-4bite2r256bs16-vi-sentence-simplification-adapter") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a01da8bb83e2b8095a06579b98051e12ff5321c35641b66e9c384ffa757dbc01
- Size of remote file:
- 1.73 GB
- SHA256:
- 3ae011e9c64cf9e7039611fed81d0cc67089ea67116d26a264b6bf05f24aae52
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.