Sentence Similarity
sentence-transformers
Safetensors
English
bert
keyphrase-ranking
text-embeddings-inference
Instructions to use sabsab129/MiniLM-searchkeys with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sabsab129/MiniLM-searchkeys with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sabsab129/MiniLM-searchkeys") 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:
- d504c6a2147735e379846a9b09b7a127be4b5bbd06c45c02ebbbb615b089df4f
- Size of remote file:
- 267 MB
- SHA256:
- 5b6636cd600b37c0bf3fee594d18c438f48583f6087497ab26f5ff252e571d4a
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