Instructions to use csebuetnlp/mT5_multilingual_XLSum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use csebuetnlp/mT5_multilingual_XLSum with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="csebuetnlp/mT5_multilingual_XLSum")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("csebuetnlp/mT5_multilingual_XLSum") model = AutoModelForSeq2SeqLM.from_pretrained("csebuetnlp/mT5_multilingual_XLSum") - Inference
- Notebooks
- Google Colab
- Kaggle
Update README.md
#9 opened over 2 years ago
by
Hezam
Update README.md
#8 opened almost 3 years ago
by
AbhishekRaghuvanshi
Adding `safetensors` variant of this model
#7 opened about 3 years ago
by
SFconvertbot
Add multilingual to the language tag
#6 opened over 3 years ago
by
lbourdois
Add verifyToken field to verify evaluation results are produced by Hugging Face's automatic model evaluator
#5 opened over 3 years ago
by
autoevaluator
Add evaluation results on the 3.0.0 config of cnn_dailymail
#2 opened almost 4 years ago
by
autoevaluator
add Rust-Language support
#1 opened almost 4 years ago
by
akitsuki