Instructions to use korben99/bne-float-384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use korben99/bne-float-384 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("korben99/bne-float-384") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bf1ad4146302a8c05c03dbed038535d41737ec05cdc02e3f0d9e96deff85b243
- Size of remote file:
- 45.1 MB
- SHA256:
- 479c6c330c3823b786448bbd57bc2cba658c5a1a1b20ce9ebaa6ee933610ff50
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