Text Retrieval
Safetensors
sentence-transformers
PyLate
xlm-roberta
ColBERT
feature-extraction
Generated from Trainer
dataset_size:118938
loss:Contrastive
Eval Results (legacy)
Instructions to use rasyosef/colbert-amharic-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use rasyosef/colbert-amharic-medium with sentence-transformers:
from pylate import models queries = [ "Which planet is known as the Red Planet?", "What is the largest planet in our solar system?", ] documents = [ ["Mars is the Red Planet.", "Venus is Earth's twin."], ["Jupiter is the largest planet.", "Saturn has rings."], ] model = models.ColBERT(model_name_or_path="rasyosef/colbert-amharic-medium") queries_emb = model.encode(queries, is_query=True) docs_emb = model.encode(documents, is_query=False) - Notebooks
- Google Colab
- Kaggle
Improve model card: update pipeline tag and add paper/code links (#1)
Browse files- Improve model card: update pipeline tag and add paper/code links (dd26fae04cb4b6f4eb038727430f9a09504435ee)
Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>
README.md
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