Sentence Similarity
sentence-transformers
ONNX
Safetensors
bert
feature-extraction
gte
mteb
Eval Results (legacy)
text-embeddings-inference
Instructions to use Mihaiii/gte-micro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Mihaiii/gte-micro with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Mihaiii/gte-micro") 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
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@@ -481,7 +481,7 @@ This is a distill of [gte-small](https://huggingface.co/thenlper/gte-small).
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## Intended purpose
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## Usage (same as [gte-small](https://huggingface.co/thenlper/gte-small))
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## Intended purpose
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<span style="color:blue">This model is designed for use in semantic-autocomplete ([click here for demo](https://mihaiii.github.io/semantic-autocomplete/)).</span>
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## Usage (same as [gte-small](https://huggingface.co/thenlper/gte-small))
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