Instructions to use menadsa/BioS-MiniLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use menadsa/BioS-MiniLM with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("menadsa/BioS-MiniLM") 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:
- 8055ad61cc9851d800569a8f1be5967ae130c41a48f5d28d16962843b72322ee
- Size of remote file:
- 90.9 MB
- SHA256:
- 84dbdf21450508ac287e5a44467ea3c47f2e664034db94af9810e917d76b9a98
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