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
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- Optimized for quick inference
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- Great at quickly generating high quality encodings
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- Easy to plug and play since it is distilled from GTE
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## Getting Started
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### Installation
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- Optimized for quick inference
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- Great at quickly generating high quality encodings
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- Easy to plug and play since it is distilled from GTE
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- **We want to see how you’re using our model so we’ll give you a free coffee/$10 gift card if you get on call with us and show us what you’ve built!**
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## Getting Started
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### Installation
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