�� Summarization

bart-large-cnn-samsum

philschmid/bart-large-cnn-samsum

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transformers
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Model Details
Full Model IDphilschmid/bart-large-cnn-samsum
Pipeline / Tasksummarization
Librarytransformers
Downloads (all-time)286.5K
Likes268
Last Modified12/23/2022
Author / Orgphilschmid
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="philschmid/bart-large-cnn-samsum")

# Run inference
result = pipe("Your input here")
print(result)
����� Tags
transformerspytorchbarttext2text-generationsagemakersummarizationendataset:samsumlicense: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.

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📊 Popularity
Downloads286.5K
����� Community Likes268
🛠�� 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?