Instructions to use saivineetha/nllb_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use saivineetha/nllb_lora with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("facebook/nllb-200-distilled-600M") model = PeftModel.from_pretrained(base_model, "saivineetha/nllb_lora") - Transformers
How to use saivineetha/nllb_lora with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("saivineetha/nllb_lora", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ae1505a13ef2c079be99750f21a9793dff72a33152e952910a2dccffa39b537
- Size of remote file:
- 5.2 kB
- SHA256:
- 644cd8d95e38c9694c2e3d4712b33deb983c899fb8173630ce5ed7289359dfc3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.