Text Classification
Transformers
PyTorch
Arabic
bert
text classification
Sentiment
text-embeddings-inference
Instructions to use Ammar-alhaj-ali/arabic-MARBERT-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ammar-alhaj-ali/arabic-MARBERT-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ammar-alhaj-ali/arabic-MARBERT-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ammar-alhaj-ali/arabic-MARBERT-sentiment") model = AutoModelForSequenceClassification.from_pretrained("Ammar-alhaj-ali/arabic-MARBERT-sentiment") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1eea188af5c237e70205af0b528b70edc07a5ef30d444d93440352cbf842eb83
- Size of remote file:
- 651 MB
- SHA256:
- b235b951f1cd9d0dcc12f723fde19500d91326bebad900f32c67db4139f2931c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.