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:
- d3e6991d8fc4075917879192176f5ebe284386cd7f02f6da3bea0fde50cfe6ed
- Size of remote file:
- 660 Bytes
- SHA256:
- 485cd50d32e47a80e688158d2046b4d1d04e042edf9d6ae98737872d5cd18e8c
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