Summarization
Transformers
PyTorch
Arabic
mbart
text2text-generation
AraBERT
BERT
BERT2BERT
MSA
Arabic Text Summarization
Arabic News Title Generation
Arabic Paraphrasing
Summarization
Generated from Trainer
Transformers
PyTorch
Instructions to use abdalrahmanshahrour/AraBART-summ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abdalrahmanshahrour/AraBART-summ 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="abdalrahmanshahrour/AraBART-summ")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("abdalrahmanshahrour/AraBART-summ") model = AutoModelForSeq2SeqLM.from_pretrained("abdalrahmanshahrour/AraBART-summ", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1 opened over 3 years ago
by
SFconvertbot