Sentence Similarity
sentence-transformers
Safetensors
English
distilbert
feature-extraction
mteb
Eval Results (legacy)
text-embeddings-inference
Instructions to use prdev/mini-gte with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use prdev/mini-gte with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("prdev/mini-gte") 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] - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 37f7b4e19bfa1e0a23e309df9f332fa681d6502dacda2951c2795606c179821f
- Size of remote file:
- 265 MB
- SHA256:
- abaa3ca6ba670db88b0d70cf33d5545e3b45f7cb03d620accf05c7bc8974ea51
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