Instructions to use malhajj/ArabGlossBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use malhajj/ArabGlossBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="malhajj/ArabGlossBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("malhajj/ArabGlossBERT") model = AutoModelForSequenceClassification.from_pretrained("malhajj/ArabGlossBERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f063e215a4d3966e53f625e2061c014e41c5fd1445f6390d5c75435c1582c52a
- Size of remote file:
- 541 MB
- SHA256:
- 2fa84e731c261772813dd74bfff1e7cb73ff3acd8fbf06b558ef7e4ce4520bf5
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