textualization/sentence-transphormers

Compute Sentence Transformer embeddings using ONNX framework.

v0.0.8 2024-02-21 00:13 UTC

This package is auto-updated.

Last update: 2024-02-21 00:13:39 UTC


README

This brings the power of Sentence Transformers to the PHP world.

Installation

Add this project to your dependencies

composer require textualization/sentence-transphormers
composer update

Before using it, you will need to install the ONNX framework:

composer exec -- php -r "require 'vendor/autoload.php'; OnnxRuntime\Vendor::check();"

and download the Distill RoBERTa v1 ONNX model (this takes a while, the model is 362Mb in size):

composer exec -- php -r "require 'vendor/autoload.php'; Textualization\SentenceTransphormers\Vendor::check();"

Multilingual model

To use the multilingual model. Additional dependencies are needed.

Download the SentencePiece library:

composer exec -- php -r "require 'vendor/autoload.php'; Textualization\SentencePiece\Vendor::check();"

Download the XLM Tokenizer SentencePiece BPE model:

composer exec -- php -r "require 'vendor/autoload.php'; Textualization\Ropherta\Tokenizer\Vendor::check();"

Download the Multilingual-E5-small model (471Mb in size):

composer exec -- php -r "require 'vendor/autoload.php'; Textualization\SentenceTransphormers\Vendor::check(true);"

Please note: if you had downloaded the monolingual model you'll need to delete it first. Currently only one model is possible, this limitation will be lifted in future versions.

Computing embeddings

$model = new SentenceRophertaModel();

$emb = $model->embeddings("Text");

Check \Textualization\Ropherta\Distances to check whether two embeddings are closer to each other.

Model employed

The model being used is an ONNX export from sentence-transformers/all-distilroberta-v1, hosted at HuggingFace Hub: textualization/all-distilroberta-v1.

The multilingual model is intfloat/multilingual-e5-small, exported to ONNX by the authors.