📝 Summarization

bart-large-cnn

facebook/bart-large-cnn

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1.9M
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transformers
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Model Details
Full Model IDfacebook/bart-large-cnn
Pipeline / Tasksummarization
Librarytransformers
Downloads (all-time)1.9M
Likes1.6K
Last Modified2/13/2024
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("summarization", model="facebook/bart-large-cnn")

# Run inference
result = pipe("Your input here")
print(result)
🏷️ Tags
transformerspytorchtfjaxrustsafetensorsbarttext2text-generationsummarizationendataset:cnn_dailymailarxiv:1910.13461license:mitmodel-indexendpoints_compatibledeploy:azureregion:us
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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: Summarization

This model is designed for the Summarization task. Explore more models for this use case.

All Summarization Models →
📊 Popularity
Downloads1.9M
❤️ Community Likes1.6K
🛠️ 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?