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:
- 4d7ba581628c2e656d6de12c8aef3eac9c9244d6dd151da417029b23324fa3ff
- Size of remote file:
- 32.2 MB
- SHA256:
- b3be18cc91c94d4a1d83731ace4dac0b90a7db024edecdeb9fe7d19ec01ce901
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