📝 Summarization

kobart-summary-v3

EbanLee/kobart-summary-v3

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46.4K
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22
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8
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transformers
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Model Details
Full Model IDEbanLee/kobart-summary-v3
Pipeline / Tasksummarization
Librarytransformers
Downloads (all-time)46.4K
Likes22
Last Modified3/13/2025
Author / OrgEbanLee
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="EbanLee/kobart-summary-v3")

# Run inference
result = pipe("Your input here")
print(result)
🏷️ Tags
transformerssafetensorsbarttext2text-generationsummarizationkoendpoints_compatibleregion: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
Downloads46.4K
❤️ Community Likes22
🛠️ 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?