Instructions to use akhooli/xlm-r-large-arabic-sent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akhooli/xlm-r-large-arabic-sent with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="akhooli/xlm-r-large-arabic-sent")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("akhooli/xlm-r-large-arabic-sent") model = AutoModelForSequenceClassification.from_pretrained("akhooli/xlm-r-large-arabic-sent") - Notebooks
- Google Colab
- Kaggle
xlm-r-large-arabic-sent
Multilingual sentiment classification (Label_0: mixed, Label_1: negative, Label_2: positive) of Arabic reviews by fine-tuning XLM-Roberta-Large.
Zero shot classification of other languages (also works in mixed languages - ex. Arabic & English). Mixed category is not accurate and may confuse other
classes (was based on a rate of 3 out of 5 in reviews).
Usage: see last section in this Colab notebook
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