🌐 Translation

nllb-200-distilled-600M

facebook/nllb-200-distilled-600M

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1.2M
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transformers
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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
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🚀 Use This Model

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.
👋 Need help with code?