Sentence Similarity
sentence-transformers
PyTorch
ONNX
Safetensors
OpenVINO
English
bert
mteb
Sentence Transformers
Eval Results (legacy)
text-embeddings-inference
Instructions to use thenlper/gte-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use thenlper/gte-large with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("thenlper/gte-large") 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 openvino model 'openvino_model.xml' (#22)
Browse files- Add exported openvino model 'openvino_model.xml' (e54741dfb10c251931f395d2f8f58c4ca28c1d81)
Co-authored-by: Tom Aarsen <tomaarsen@users.noreply.huggingface.co>
openvino/openvino_model.bin
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version https://git-lfs.github.com/spec/v1
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openvino/openvino_model.xml
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