Summarization
Transformers
Safetensors
Arabic
t5
text2text-generation
arabic
arabic-nlp
arat5
huggingface
fine-tuned
text-generation-inference
Instructions to use fatmaserry/AraT5v2-arabic-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fatmaserry/AraT5v2-arabic-summarization 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="fatmaserry/AraT5v2-arabic-summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("fatmaserry/AraT5v2-arabic-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("fatmaserry/AraT5v2-arabic-summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
warning : need to be updated
#1
by superAhmed91 - opened
there is error related to transformer version need to be fixed
for not long talk
with the new transformers ..run this
from transformers import AutoTokenizer
model_name = 'fatmaserry/AraT5v2-arabic-summarization'
tokenizer = AutoTokenizer.from_pretrained(model_name)
the one that worked due to slight newer transformers version is eslamxm/AraT5v2-base-1024-finetuned-ar-wikilingua