sentence-transformers
ONNX
Safetensors
English
ogma
mteb
embedding
text-embedding
axiotic
matryoshka
small-model
custom_code
Eval Results (legacy)
Instructions to use axiotic/ogma-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use axiotic/ogma-large with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("axiotic/ogma-large", trust_remote_code=True) sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Commit History
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fix(docs): retrieval uses task=qry for both queries and docs 5526648
docs: remove CPU inference benchmark table 0b8e0dc
fix(docs): correct retrieval example to symmetric encoding 7040ad5
Add OgmaTokenizerFast + model.embed() high-level API 1e6ff58
Remove hedging from public model card d66fb10
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Clean public model card provenance wording 2fb5682
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