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
Commit History
-
Fix typo in model name
Prashanth Raod386cc1
-
Update README.md
ae61f0c -
Update README.md
34ae007 -
Update README.md
2b1a85a
-
Adding ONNX file of this model (#2)
- Adding ONNX file of this model (829fea06b9971d6e924ceab9ca6852feebc069c0) Co-authored-by: CHRISTOPHER FLEETWOOD <FL33TW00D@users.noreply.huggingface.co>5b7a05d
-
Upload modules.json
f698b56
-
Update README.md
34329e5 -
Upload 2 files
869e8f6
-
add tags
72e1b62
-
Update README.md
9616e37 -
Update README.md
74608dd -
Update README.md
bd2a035 -
Update README.md
52836b6 -
Update README.md
823d856
-
Update README.md
d90a6d9 -
Upload vocab.txt
7b1b11e -
Upload tokenizer.json
9d9f839 -
Upload tokenizer_config.json
e2c3ce8 -
Upload special_tokens_map.json
5b5748d -
Upload config.json
8bd7d0c -
Upload pytorch_model.bin
7f39506 -
initial commit
baa4cd6