Sentence Similarity
sentence-transformers
PyTorch
ONNX
Safetensors
OpenVINO
English
bert
mteb
Sentence Transformers
Eval Results (legacy)
text-embeddings-inference
Instructions to use thenlper/gte-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use thenlper/gte-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("thenlper/gte-base") 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
Add exported onnx model 'model_O4.onnx'
#13
by tomaarsen HF Staff - opened
- onnx/model_O4.onnx +3 -0
onnx/model_O4.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:ee7ebf70ed3c3e8da7961b3be37e5d865482da52ec6b814d25705bdfe8a6aa62
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size 217824059
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