https://github.com/davidberenstein1957/fast-sentence-transformers
Simply, faster, sentence-transformers
https://github.com/davidberenstein1957/fast-sentence-transformers
embeddings hacktoberfest nlp onnx sentence-transformers
Last synced: about 2 months ago
JSON representation
Simply, faster, sentence-transformers
- Host: GitHub
- URL: https://github.com/davidberenstein1957/fast-sentence-transformers
- Owner: davidberenstein1957
- License: mit
- Created: 2022-04-20T14:03:01.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2024-08-27T07:38:17.000Z (about 1 year ago)
- Last Synced: 2025-07-09T14:12:23.819Z (3 months ago)
- Topics: embeddings, hacktoberfest, nlp, onnx, sentence-transformers
- Language: Python
- Homepage:
- Size: 456 KB
- Stars: 143
- Watchers: 4
- Forks: 10
- Open Issues: 5
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Citation: CITATION.cff
Awesome Lists containing this project
README
# Fast Sentence Transformers
This repository contains code to run faster feature extractors using tools like quantization, optimization and `ONNX`. Just run your model much faster, while using less of memory. There is not much to it!
[](https://github.com/Pandora-Intelligence/fast-sentence-transformers/actions/workflows/python-package.yml)
[](https://github.com/pandora-intelligence/fast-sentence-transformers/releases)
[](https://pypi.org/project/fast-sentence-transformers/)
[](https://pypi.org/project/fast-sentence-transformers/)
[](https://github.com/ambv/black)> [Phillip Schmid](https://www.philschmid.de/optimize-sentence-transformers): "We successfully quantized our vanilla Transformers model with Hugging Face and managed to accelerate our model latency from 25.6ms to 12.3ms or 2.09x while keeping 100% of the accuracy on the stsb dataset.
> But I have to say that this isn't a plug and play process you can transfer to any Transformers model, task or dataset.""## Install
```bash
pip install fast-sentence-transformers
```Or, for GPU support:
```bash
pip install fast-sentence-transformers[gpu]
```## Quickstart
```python
from fast_sentence_transformers import FastSentenceTransformer as SentenceTransformer
# use any sentence-transformer
encoder = SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2", device="cpu")encoder.encode("Hello hello, hey, hello hello")
encoder.encode(["Life is too short to eat bad food!"] * 2)
```## Benchmark
Non-exact, indicative benchmark for speed an memory usage with smaller and larger model on `sentence-transformers`
| model | Type | default | ONNX | ONNX+quantized | ONNX+GPU |
| ------------------------------------- | ------ | ------- | ---- | -------------- | -------- |
| paraphrase-albert-small-v2 | memory | 1x | 1x | 1x | 1x |
| | speed | 1x | 2x | 5x | 20x |
| paraphrase-multilingual-mpnet-base-v2 | memory | 1x | 1x | 4x | 4x |
| | speed | 1x | 2x | 5x | 20x |## Shout-Out
This package heavily leans on https://www.philschmid.de/optimize-sentence-transformers.