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
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
light_embed-0.1.7.tar.gz
(12.9 kB
view details)
Built Distribution
File details
Details for the file light_embed-0.1.7.tar.gz
.
File metadata
- Download URL: light_embed-0.1.7.tar.gz
- Upload date:
- Size: 12.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.10.14
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 49eb208c6546ae8fce56c7ad2abfe419d848bac58a927e2743228c13a7755712 |
|
MD5 | 83507dde9fec7f1bb939a5213bbd5bfb |
|
BLAKE2b-256 | 44ec098acae91a5f011099a26572364dbde92f4bb456f64329989fc01d0d4741 |
File details
Details for the file light_embed-0.1.7-py3-none-any.whl
.
File metadata
- Download URL: light_embed-0.1.7-py3-none-any.whl
- Upload date:
- Size: 15.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.10.14
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 9681d4fe2d65bb4e78c66650e3918e41142e52f14cfd39cb6adcfb950db15bb9 |
|
MD5 | 664664edc983dc577945bebe5f9ac16c |
|
BLAKE2b-256 | dcbdb22e3db754aa70fa354b5db604af94ca127fe85e86cda9ae6e17b58bd142 |