Instructions to use Matankl/arabert-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Matankl/arabert-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Matankl/arabert-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Matankl/arabert-classification") model = AutoModelForSequenceClassification.from_pretrained("Matankl/arabert-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Matankl/arabert-classification: direct link, hf CLI and curl.
- Browser
- Download file 4.41 kB
-
https://huggingface.co/Matankl/arabert-classification/resolve/main/training_args.bin
- Command line
-
hf download hf://Matankl/arabert-classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Matankl/arabert-classification/resolve/main/training_args.bin
4.41 kB
- Xet hash:
- 20be09d042ae473682b8409b109a44f1245636ef132952e18670bccdb47af89c
- Size of remote file:
- 4.41 kB
- SHA256:
- 2f4da2e2d3a7d086fcc319b85a60fc58358ffaf62dc9264468b7c0ce0b65403a
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