---
language:
- ar
metrics:
- accuracy
- bleu
library_name: transformers
pipeline_tag: text2text-generation
---
This model is under trial.

The number in the generated text represents the category of the news, as shown below.
category_mapping = {

    'Political':1,
    'Economy':2,
    'Health':3,
    'Sport':4,
    'Culture':5,
    'Technology':6,
    'Art':7,
    'Accidents':8
}

![image/png](https://cdn-uploads.huggingface.co/production/uploads/645817bb72b60ae7a37f8f40/6gZDjcAOhWLvN5xF-E2FE.png)

# Example usage
model_name = "Hezam/arabic-T5-news-classification-generation"
from transformers import T5ForConditionalGeneration, T5Tokenizer
model = T5ForConditionalGeneration.from_pretrained(model_name)
tokenizer = T5Tokenizer.from_pretrained(model_name)
input_text = " الاستاذ حزام جوبح يحصل على براعة اختراع في التعلم العميق"

output_text = model.generate(input_text)

print(generated_text)