from light_embed import TextEmbedding
sentences = [
	"This is an example sentence",
	"Each sentence is converted"
]

model = TextEmbedding('sentence-transformers/all-MiniLM-L6-v2')
embeddings = model.encode(sentences)
print(embeddings)

or by specifying the onnx model name like this:

python

from light_embed import TextEmbedding
sentences = [
	"This is an example sentence",
	"Each sentence is converted"
]

model = TextEmbedding('onnx-models/all-MiniLM-L6-v2-onnx')
embeddings = model.encode(sentences)
print(embeddings)

Citing & Authors

Binh Nguyen / binhcode25@gmail.com

kurtletoez/all-MiniLM-L6-v2-onnx

onnx-models/all-MiniLM-L6-v2-onnx

Model details

Usage

Citing & Authors

kurtletoez/
all-MiniLM-L6-v2-onnx