textualization / sentence-transphormers
Compute Sentence Transformer embeddings using ONNX framework.
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Ko-Fi
Requires
- ankane/onnxruntime: v0.1.7
- textualization/ropherta: v0.0.11
Requires (Dev)
- phpunit/phpunit: ^9.5.8
README
Compute RoBERTa sentence embeddings in PHP using ONNX framework.
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.