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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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.