Sentence Similarity
Safetensors
sentence-transformers
PyLate
xlm-roberta
ColBERT
feature-extraction
Generated from Trainer
dataset_size:121666
loss:Contrastive
Eval Results (legacy)
text-embeddings-inference
Instructions to use yosefw/colbert-roberta-amharic-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use yosefw/colbert-roberta-amharic-base 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="yosefw/colbert-roberta-amharic-base") queries_emb = model.encode(queries, is_query=True) docs_emb = model.encode(documents, is_query=False) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3b79871f7ed4ddf45eb082f78943ccde8b1501336a9d3f9dedc6c07e0659c024
- Size of remote file:
- 442 MB
- SHA256:
- efdc9185ab356151fc296b22522b85c425eda3912577e39acc2895cc226b7ff2
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