Text Classification
Transformers
PyTorch
Safetensors
Arabic
bert
Trained with AutoTrain
text-embeddings-inference
Instructions to use U4RASD/ArATTC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use U4RASD/ArATTC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="U4RASD/ArATTC")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("U4RASD/ArATTC") model = AutoModelForSequenceClassification.from_pretrained("U4RASD/ArATTC") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 71664ea0739d59a21144e7c571caac5df46258b59d693188398e6e12170101fb
- Size of remote file:
- 541 MB
- SHA256:
- b2d541447e286f03cb40b8ac969451592ac244b396ee706f51f7392af6233c6a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.