�� Summarization

kobart-summary-v3

EbanLee/kobart-summary-v3

Get AI Model →
64.5K
Downloads
�����
22
Likes
�����
8
Tags
📦
transformers
Library
Model Details
Full Model IDEbanLee/kobart-summary-v3
Pipeline / Tasksummarization
Librarytransformers
Downloads (all-time)64.5K
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
More Summarization Models
See all →
t5-small

google-t5/t5-small

3.3M����� 550
Get AI Model →
t5-base

google-t5/t5-base

2.2M����� 776
Get AI Model →
bart-large-cnn

facebook/bart-large-cnn

1.9M����� 1.6K
Get AI Model →
🚀 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
Downloads64.5K
����� 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?