onnx-models/all-MiniLM-L6-v2-fine-tuned-epochs-8-onnx
This is the ONNX-ported version of the event-nlp/all-MiniLM-L6-v2-fine-tuned-epochs-8 for generating text embeddings.
Model details
- Embedding dimension: 384
- Max sequence length: 256
- File size on disk: 0.08 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:
from light_embed import TextEmbedding
sentences = [
"This is an example sentence",
"Each sentence is converted"
]
model = TextEmbedding('event-nlp/all-MiniLM-L6-v2-fine-tuned-epochs-8')
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/all-MiniLM-L6-v2-fine-tuned-epochs-8-onnx')
embeddings = model.encode(sentences)
print(embeddings)
Citing & Authors
Binh Nguyen / binhcode25@gmail.com
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