📝 Summarization

mT5_multilingual_XLSum

csebuetnlp/mT5_multilingual_XLSum

Get AI Model →
48.4K
Downloads
❤️
325
Likes
🏷️
54
Tags
📦
transformers
Library
Model Details
Full Model IDcsebuetnlp/mT5_multilingual_XLSum
Pipeline / Tasksummarization
Librarytransformers
Downloads (all-time)48.4K
Likes325
Last Modified8/13/2022
Author / Orgcsebuetnlp
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="csebuetnlp/mT5_multilingual_XLSum")

# Run inference
result = pipe("Your input here")
print(result)
🏷️ Tags
transformerspytorchmt5text2text-generationsummarizationmT5amarazbnmyzhenfrguhahiigidjarnkokymrneompsfapcmpt
More Summarization Models
See all →
t5-small

google-t5/t5-small

2.2M❤️ 542
Get AI Model →
bart-large-cnn

facebook/bart-large-cnn

1.9M❤️ 1.6K
Get AI Model →
t5-base

google-t5/t5-base

1.4M❤️ 773
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
Downloads48.4K
❤️ Community Likes325
🛠️ 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?