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onnx-models/Splade_PP_en_v1-onnx
Splade_PP_en_v1-onnx is a sentence similarity model from onnx-models. Use it when you need a score for how close two texts are. It is set up for light-embed.
This is the ONNX-ported version of the prithivida/SpladePPenv1 for generating text embeddings.
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From the Hugging Face model README
This is the ONNX-ported version of the prithivida/Splade_PP_en_v1 for generating text embeddings.
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('prithivida/Splade_PP_en_v1')
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/Splade_PP_en_v1-onnx')
embeddings = model.encode(sentences)
print(embeddings)
Binh Nguyen / [email protected]