Text Ranking
sentence-transformers
Safetensors
xlm-roberta
cross-encoder
reranker
Generated from Trainer
dataset_size:246013
loss:BinaryCrossEntropyLoss
text-embeddings-inference
Instructions to use leafxyz/arabic-ecom-cross-encoder-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use leafxyz/arabic-ecom-cross-encoder-v3 with sentence-transformers:
from sentence_transformers import CrossEncoder model = CrossEncoder("leafxyz/arabic-ecom-cross-encoder-v3") query = "Which planet is known as the Red Planet?" passages = [ "Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." ] scores = model.predict([(query, passage) for passage in passages]) print(scores) - Notebooks
- Google Colab
- Kaggle
File size: 133 Bytes
599e1dc | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:7ef4dd5924152f80fdfe441d154ab14d6d04e5ae9f0c52113b4d4412d681c800
size 16766387
|