Instructions to use MCAA1-MSU/mcaaiNLLB with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use MCAA1-MSU/mcaaiNLLB 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, "MCAA1-MSU/mcaaiNLLB") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a9221d246679b8ed3247b1327237c2eb3ad6fb56c6df6a4e807c5d4410d56be8
- Size of remote file:
- 37.9 MB
- SHA256:
- 1eecc668a2dd6207a8d34f5c733baec09b37da4444412683a5610addff7194a7
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