Sentence Similarity
ONNX
sentence-transformers
light-embed
bert
feature-extraction
text-embeddings-inference
Instructions to use LightEmbed/sbert-all-MiniLM-L6-v2-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use LightEmbed/sbert-all-MiniLM-L6-v2-onnx with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("LightEmbed/sbert-all-MiniLM-L6-v2-onnx") 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] - Notebooks
- Google Colab
- Kaggle
Commit History
-
Add new SentenceTransformer model.
Verified signaturebfd894e
-
Add new SentenceTransformer model.
Verified signaturec3ed879 -
Add new SentenceTransformer model.
Verified signature4223aa7 -
Add new SentenceTransformer model.
Verified signature3e8c9bf -
Add new SentenceTransformer model.
Verified signatureeb30144
-
Add new SentenceTransformer model.
Verified signaturea0f3972
-
remove redundant files
nguyenthaibinhd792ef7 -
Add new SentenceTransformer model.
Verified signature132ae0e
-
Add new SentenceTransformer model.
Verified signaturec0d3062 -
Add new SentenceTransformer model.
Verified signature97dea54 -
Add new SentenceTransformer model.
Verified signature7b4d389 -
Add new SentenceTransformer model.
Verified signature6050c34
-
add base model name
nguyenthaibinh13a8a84 -
fixed typo error
nguyenthaibinh0ee66b4 -
add model_info.json
nguyenthaibinh414552d
-
changed onnx model file name
nguyenthaibinhd828993
-
upload json config files
nguyenthaibinh0c4496a -
Upload quantized_false.onnx
Verified signature63b43ef -
initial commit
Verified signature2989554