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all-mpnet-base-v2-fine-tuned-epochs-1-onnx – AI Model by onnx-models | AlphaNeural AI

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onnx-models/
all-mpnet-base-v2-fine-tuned-epochs-1-onnx

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sentence-transformers

feature-extraction

sentence-similarity

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onnx-models/all-mpnet-base-v2-fine-tuned-epochs-1-onnx

This is the ONNX-ported version of the event-nlp/all-mpnet-base-v2-fine-tuned-epochs-1 for generating text embeddings.

Model details

Embedding dimension: 768
Max sequence length: 384
File size on disk: 0.41 GB
Modules incorporated in the onnx: Transformer, Pooling, Normalize

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:

python

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

model = TextEmbedding('event-nlp/all-mpnet-base-v2-fine-tuned-epochs-1')
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-mpnet-base-v2-fine-tuned-epochs-1-onnx')
embeddings = model.encode(sentences)
print(embeddings)

Citing & Authors

Binh Nguyen / binhcode25@gmail.com