Sentence Similarity
sentence-transformers
Safetensors
multilingual
modernbert
embeddings
feature-extraction
matryoshka
retrieval
text-embeddings-inference
Instructions to use hotchpotch/bekko-embedding-v1-a8m-pt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use hotchpotch/bekko-embedding-v1-a8m-pt with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("hotchpotch/bekko-embedding-v1-a8m-pt") 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:
- daf46a52874fb9b6191b9ae46a0f471904405b611f8e1d580f76c7424d343f89
- Size of remote file:
- 34.4 MB
- SHA256:
- 17f7d8b9518c403d7429ad9eeeabb6eed49c8d3311de8ef4ed5ad811381a2ced
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