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Fast and Lightweight Text Embedding

Project description

LightEmbed

LightEmbed is a light-weight, fast, and efficient tool for generating sentence embeddings. It does not rely on heavy dependencies like PyTorch and Transformers, making it suitable for environments with limited resources.

Benefits

1. Light-weight

  • Minimal Dependencies: LightEmbed does not depend on PyTorch and Transformers.
  • Low Resource Requirements: Operates smoothly with minimal specs: 1GB RAM, 1 CPU, and no GPU required.

2. Fast (as light)

  • ONNX Runtime: Utilizes the ONNX runtime, which is significantly faster compared to Sentence Transformers that use PyTorch.

3. Same as Original Sentence Transformers' Outputs

  • Consistency: Incorporates all modules from a Sentence Transformer model, including normalization and pooling.
  • Accuracy: Produces embedding vectors identical to those from Sentence Transformers.

Installation

pip install -U light-embed

Usage

Then you can use the model like this:

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

model = TextEmbedding('sentence-transformers-model-name')
embeddings = model.encode(sentences)
print(embeddings)

For example:

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)

Citing & Authors

Binh Nguyen / binhcode25@gmail.com

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