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-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use rasyosef/reranker-amharic-medium with sentence-transformers:
from sentence_transformers import CrossEncoder model = CrossEncoder("rasyosef/reranker-amharic-medium") 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
Improve model card: add paper, code links and citation
#2
by nielsr HF Staff - opened
This PR improves the model card for reranker-amharic-medium by:
- Adding a link to the associated research paper: "The Multilingual Curse at the Retrieval Layer: Evidence from Amharic".
- Adding a link to the official GitHub repository.
- Updating the usage section with a slightly more descriptive example from the GitHub README.
- Including the BibTeX citation for researchers using this model.
rasyosef changed pull request status to merged