Visual Document Retrieval
sentence-transformers
Safetensors
Arabic
qwen3_vl
sentence-similarity
feature-extraction
Generated from Trainer
dataset_size:48002
loss:MatryoshkaLoss
loss:CachedMultipleNegativesRankingLoss
Instructions to use Omartificial-Intelligence-Space/Qwen3-VL-Embedding-2B-Arabic-VDR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Omartificial-Intelligence-Space/Qwen3-VL-Embedding-2B-Arabic-VDR with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Omartificial-Intelligence-Space/Qwen3-VL-Embedding-2B-Arabic-VDR") sentences = [ "بناءً على ما يظهر في الصورة، كيف يمكن تفسير تكيف هذا الطائر مع بيئته الصخرية والصحراوية؟", "Fauna", "Flora", "Oman" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K