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
- Xet hash:
- 134f914e141c194490a584aac09d6937a3a668bfd7c58843bc263a62cd32855a
- Size of remote file:
- 7.68 MB
- SHA256:
- e00a98d8b3d4625c532233d0672ea8ed0b97ef5eaca163b612f1645fa00d2fc3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.