Summarization
Transformers
PyTorch
TensorBoard
mt5
text2text-generation
mT5_multilingual_XLSum
abstractive summarization
ar
xlsum
Generated from Trainer
Instructions to use ahmeddbahaa/mT5_multilingual_XLSum-finetune-ar-xlsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ahmeddbahaa/mT5_multilingual_XLSum-finetune-ar-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="ahmeddbahaa/mT5_multilingual_XLSum-finetune-ar-xlsum")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ahmeddbahaa/mT5_multilingual_XLSum-finetune-ar-xlsum") model = AutoModelForSeq2SeqLM.from_pretrained("ahmeddbahaa/mT5_multilingual_XLSum-finetune-ar-xlsum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
#2 opened over 2 years ago
by
librarian-bot
Adding `safetensors` variant of this model
#1 opened almost 3 years ago
by
SFconvertbot