Instructions to use sultan/ArabicTransformer-small-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sultan/ArabicTransformer-small-encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="sultan/ArabicTransformer-small-encoder")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sultan/ArabicTransformer-small-encoder") model = AutoModel.from_pretrained("sultan/ArabicTransformer-small-encoder") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 67e36eb79875f8c1926b6cd1f501fa319e37a697d1bbf94d78b3a61bdcdfe8d5
- Size of remote file:
- 522 MB
- SHA256:
- 166293638511f21ecd8d7fe5f1d32b7a2fc52c933e2890b817520ebd2b409cbc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.