Text Classification
Transformers
PyTorch
Safetensors
Arabic
Egyptian Arabic
Moroccan Arabic
bert
text-embeddings-inference
Instructions to use IbrahimAmin/marbertv2-arabic-written-dialect-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IbrahimAmin/marbertv2-arabic-written-dialect-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="IbrahimAmin/marbertv2-arabic-written-dialect-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IbrahimAmin/marbertv2-arabic-written-dialect-classifier") model = AutoModelForSequenceClassification.from_pretrained("IbrahimAmin/marbertv2-arabic-written-dialect-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- df24bcc8f206b0432d39aa448b0fb8bdf2e2641ad441e63b3429e64b7f17e66f
- Size of remote file:
- 4.09 kB
- SHA256:
- db4bf47c8226b4f46448345533723c7b8978fcdc9a41bf07b74b3ed5932f3822
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