Sentence Similarity
sentence-transformers
PyTorch
Safetensors
Transformers
Arabic
bert
feature-extraction
Hadith
Islam
Arabic
text-embeddings-inference
Instructions to use FDSRashid/QulBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use FDSRashid/QulBERT with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("FDSRashid/QulBERT") sentences = [ "هذا شخص سعيد", "هذا كلب سعيد", "هذا شخص سعيد جدا", "اليوم هو يوم مشمس" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use FDSRashid/QulBERT with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("FDSRashid/QulBERT") model = AutoModel.from_pretrained("FDSRashid/QulBERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bccdc5755b63a7773b6daa449c2090e4c656f090fc99dd469669cb47eb258693
- Size of remote file:
- 436 MB
- SHA256:
- 6a555179611d4e349f638527ccd1dcc5f96012a39c50f30fb2f03450386b29bf
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