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
- Xet hash:
- 092c27e58bb354ec1ef3c1fa053d3cf70b716edd2d6ecb766ed539bd912b84d3
- Size of remote file:
- 66.8 MB
- SHA256:
- 344099675ecefb2dc886e6dcc1fba7ccc0c66dbf455e8aa289035ee8d688f125
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