Instructions to use Tung177/gemma-2-2b-4bit-1e-4-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-4bit-1e-4-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-4bit-1e-4-vi-sentence-simplification-adapter") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 11ec05e6793d1403eff480422900d816ef20b4ee2cc25b59f0f1dc1dea15e867
- Size of remote file:
- 1.73 GB
- SHA256:
- 1395c2f15d75c351ed8cc9f7cbedfc8b4dec993d98f5ff7151ce3dea64de5934
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.