Text Ranking
sentence-transformers
Safetensors
Amharic
xlm-roberta
cross-encoder
Generated from Trainer
dataset_size:491752
loss:BinaryCrossEntropyLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use rasyosef/reranker-amharic-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use rasyosef/reranker-amharic-base with sentence-transformers:
from sentence_transformers import CrossEncoder model = CrossEncoder("rasyosef/reranker-amharic-base") 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
Add paper and code links to model card
#1
by nielsr HF Staff - opened
This PR improves the model card by adding a link to the research paper "The Multilingual Curse at the Retrieval Layer: Evidence from Amharic" and the official source code repository. It also adds the BibTeX citation and slightly updates the usage snippet to match the examples found in the official repository.
rasyosef changed pull request status to merged