Text Classification
Transformers
Safetensors
Arabic
bert
arabic
nlp
saudi
dialectal-arabic
complaints
restaurant-reviews
aspect-classification
ambience-detection
Eval Results (legacy)
text-embeddings-inference
Instructions to use FerasMad/arabic-complaints-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FerasMad/arabic-complaints-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="FerasMad/arabic-complaints-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("FerasMad/arabic-complaints-classifier") model = AutoModelForSequenceClassification.from_pretrained("FerasMad/arabic-complaints-classifier") - Notebooks
- Google Colab
- Kaggle
File size: 230 Bytes
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