Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Anwaarma/Arabert-twitter-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Anwaarma/Arabert-twitter-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Anwaarma/Arabert-twitter-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Anwaarma/Arabert-twitter-sentiment") model = AutoModelForSequenceClassification.from_pretrained("Anwaarma/Arabert-twitter-sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a661c863f3ebc199d2b519d43ee0c8c50f23293821e163aea65895a16767d83
- Size of remote file:
- 4.47 kB
- SHA256:
- aeee0f0ac771e6268e4cd860ca08919bf1927335066c2f0db8b4862a622a8095
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