Sentence Similarity
sentence-transformers
ONNX
Safetensors
OpenVINO
multilingual
modernbert
embeddings
feature-extraction
matryoshka
retrieval
text-embeddings-inference
Instructions to use hotchpotch/bekko-embedding-v1-a25m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use hotchpotch/bekko-embedding-v1-a25m with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("hotchpotch/bekko-embedding-v1-a25m") 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] - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5a4bfdd0d481324e263406e302c001a99489c96f8664cc15b8cd8c84526d9c1d
- Size of remote file:
- 493 MB
- SHA256:
- 49a667898c1a314a29417c23da9a6539255aa7fa98ecedd0e8311e172a44c976
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