Text Classification
Transformers
PyTorch
Arabic
bert
sentiment analysis
classification
arabic dialect
tunisian dialect
Instructions to use AhmedBou/TuniBert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AhmedBou/TuniBert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AhmedBou/TuniBert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AhmedBou/TuniBert") model = AutoModelForSequenceClassification.from_pretrained("AhmedBou/TuniBert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 46859b0db15d1b08eb2369129a359d32b8c3f872c47b32df5505b3d04203cb67
- Size of remote file:
- 443 MB
- SHA256:
- 76d08ff929663495f99547413cf1952e31cc64affec2be01d452dd8ea420262b
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