Instructions to use sultan/ArabicTransformer-base-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sultan/ArabicTransformer-base-encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="sultan/ArabicTransformer-base-encoder")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sultan/ArabicTransformer-base-encoder") model = AutoModel.from_pretrained("sultan/ArabicTransformer-base-encoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from sultan/ArabicTransformer-base-encoder: direct link, hf CLI and curl.
- Browser
- Download file 707 MB
-
https://huggingface.co/sultan/ArabicTransformer-base-encoder/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://sultan/ArabicTransformer-base-encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sultan/ArabicTransformer-base-encoder/resolve/main/pytorch_model.bin
707 MB
- Xet hash:
- e0dbdfc43416b3c3878c19a4dada28190c46642421320cc83d8f8a1530fbfdb6
- Size of remote file:
- 707 MB
- SHA256:
- 7d80c4651affe485eebb0ae33db631dd72e2c49327dd6a09135aa6042d321f54
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