Instructions to use metga97/Modern-EgyBert-Embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use metga97/Modern-EgyBert-Embedding with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="metga97/Modern-EgyBert-Embedding")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("metga97/Modern-EgyBert-Embedding") model = AutoModel.from_pretrained("metga97/Modern-EgyBert-Embedding", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from metga97/Modern-EgyBert-Embedding: direct link, hf CLI and curl.
- Browser
- Download file 6.27 MB
-
https://huggingface.co/metga97/Modern-EgyBert-Embedding/resolve/main/tokenizer.json
- Command line
-
hf download hf://metga97/Modern-EgyBert-Embedding/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/metga97/Modern-EgyBert-Embedding/resolve/main/tokenizer.json
6.27 MB
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