Model Details
Full Model IDcsebuetnlp/mT5_multilingual_XLSum
Pipeline / Tasksummarization
Librarytransformers
Downloads (all-time)21.2K
Likes326
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
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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
⬇ Downloads21.2K
����� Community Likes326
🛠�� 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.