Model Details
Full Model IDfacebook/nllb-200-distilled-600M
Pipeline / Tasktranslation
Librarytransformers
Downloads (all-time)1.2M
Likes885
Last Modified2/14/2024
Author / Orgfacebook
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("translation", model="facebook/nllb-200-distilled-600M")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerspytorchm2m_100text2text-generationnllbtranslationaceacmacqaebafajpakalsamapcararsaryarzasastawaayrazbazjbabmbanbe
More Translation Models
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Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models🌐 Task: Translation
This model is designed for the Translation task. Explore more models for this use case.
All Translation Models →📊 Popularity
⬇ Downloads1.2M
❤️ Community Likes885
🛠️ Requirements
- →Install: pip install transformers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.