onnx-models/jina-embeddings-v2-small-en-onnx
This is the ONNX-ported version of the jinaai/jina-embeddings-v2-small-en for generating text embeddings.
Model details
- Embedding dimension: 512
- Max sequence length: 8192
- File size on disk: 0.11 GB
- Modules incorporated in the onnx: Transformer, Pooling
Usage
Using this model becomes easy when you have light-embed installed:
pip install -U light-embed
Then you can use the model by specifying the original model name like this:
from light_embed import TextEmbedding
sentences = [
"This is an example sentence",
"Each sentence is converted"
]
model = TextEmbedding('jinaai/jina-embeddings-v2-small-en')
embeddings = model.encode(sentences)
print(embeddings)
or by specifying the onnx model name like this:
from light_embed import TextEmbedding
sentences = [
"This is an example sentence",
"Each sentence is converted"
]
model = TextEmbedding('onnx-models/jina-embeddings-v2-small-en-onnx')
embeddings = model.encode(sentences)
print(embeddings)
Citing & Authors
Binh Nguyen / [email protected]
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