Instructions to use SinaLab/ArabGlossBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SinaLab/ArabGlossBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SinaLab/ArabGlossBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SinaLab/ArabGlossBERT") model = AutoModelForSequenceClassification.from_pretrained("SinaLab/ArabGlossBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download examples.json from SinaLab/ArabGlossBERT: direct link, hf CLI and curl.
- Browser
- Download file 1.02 kB
-
https://huggingface.co/SinaLab/ArabGlossBERT/resolve/refs%2Fpr%2F2/examples.json
- Command line
-
hf download hf://SinaLab/ArabGlossBERT@refs/pr/2/examples.json
-
curl -L -o examples.json https://huggingface.co/SinaLab/ArabGlossBERT/resolve/refs%2Fpr%2F2/examples.json
1.02 kB
| [ | |
| { | |
| "sentence_id": 1, | |
| "sentence": "كيف ساهمت السياسة", | |
| "words": | |
| [ | |
| { | |
| "word_id": 1, | |
| "word": "كيف", | |
| "senses": [303048554, 303048555] | |
| }, | |
| { | |
| "word_id": 2, | |
| "word": "ساهمت", | |
| "senses": [303026923, 303026924, 303026925] | |
| }, | |
| { | |
| "word_id": 3, | |
| "word": "السياسة", | |
| "senses": [303027138, 303027139, 303027140, 303027141] | |
| } | |
| ] | |
| }, | |
| { | |
| "sentence_id": 2, | |
| "sentence": "الأميركية المستندة إلى", | |
| "words": | |
| [ | |
| { | |
| "word_id": 1, | |
| "word": "الأميركية", | |
| "senses": [302004373] | |
| }, | |
| { | |
| "word_id": 2, | |
| "word": "المستندة", | |
| "senses": [302053376, 302053377] | |
| }, | |
| { | |
| "word_id": 3, | |
| "word": "إلى", | |
| "senses": [303002296, 303002297, 303002298] | |
| } | |
| ] | |
| } | |
| ] |