Sentence Similarity
sentence-transformers
PyTorch
TensorFlow
Core ML
ONNX
Safetensors
OpenVINO
English
bert
mteb
Sentence Transformers
Eval Results (legacy)
text-embeddings-inference
Instructions to use thenlper/gte-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use thenlper/gte-small with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("thenlper/gte-small") 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
Download tf_model.h5 from thenlper/gte-small: direct link, hf CLI and curl.
- Browser
- Download file 134 MB
-
https://huggingface.co/thenlper/gte-small/resolve/main/tf_model.h5
- Command line
-
hf download hf://thenlper/gte-small/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/thenlper/gte-small/resolve/main/tf_model.h5
134 MB
- Xet hash:
- 1cbd856977200a717002025c53f4aa5bb658c8fb9c89b579a682a822a904d7d8
- Size of remote file:
- 134 MB
- SHA256:
- 38d78f5cca85e9bfb60faf70f29d28f0946f3d8caba6f82cc45766e8cdfdc036
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