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
Update README.md
Browse files
README.md
CHANGED
|
@@ -14,6 +14,7 @@ datasets:
|
|
| 14 |
language:
|
| 15 |
- ar
|
| 16 |
library_name: sentence-transformers
|
|
|
|
| 17 |
---
|
| 18 |
|
| 19 |
# QulBERT
|
|
|
|
| 14 |
language:
|
| 15 |
- ar
|
| 16 |
library_name: sentence-transformers
|
| 17 |
+
base_model: CAMeL-Lab/bert-base-arabic-camelbert-ca
|
| 18 |
---
|
| 19 |
|
| 20 |
# QulBERT
|