📝 Summarization

distilbart-cnn-6-6

sshleifer/distilbart-cnn-6-6

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transformers
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Model Details
Full Model IDsshleifer/distilbart-cnn-6-6
Pipeline / Tasksummarization
Librarytransformers
Downloads (all-time)26.4K
Likes33
Last Modified6/14/2021
Author / Orgsshleifer
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="sshleifer/distilbart-cnn-6-6")

# Run inference
result = pipe("Your input here")
print(result)
🏷️ Tags
transformerspytorchjaxrustbarttext2text-generationsummarizationendataset:cnn_dailymaildataset:xsumlicense:apache-2.0endpoints_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
Downloads26.4K
❤️ Community Likes33
🛠️ 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?