Feature Extraction
Transformers.js
ONNX
English
embedding_gemma2
audio
music
music-information-retrieval
text-to-audio-retrieval
embeddings
Instructions to use jaisawhney/SonicEmbed-ONNX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use jaisawhney/SonicEmbed-ONNX with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('feature-extraction', 'jaisawhney/SonicEmbed-ONNX');
Download scripts/pyproject.toml from jaisawhney/SonicEmbed-ONNX: direct link, hf CLI and curl.
- Browser
- Download file 375 Bytes
-
https://huggingface.co/jaisawhney/SonicEmbed-ONNX/resolve/main/scripts/pyproject.toml
- Command line
-
hf download hf://jaisawhney/SonicEmbed-ONNX/scripts/pyproject.toml
-
curl -L -o pyproject.toml https://huggingface.co/jaisawhney/SonicEmbed-ONNX/resolve/main/scripts/pyproject.toml
375 Bytes
| [project] | |
| name = "sonicembed-onnx" | |
| version = "0.1.0" | |
| description = "Scores the SonicEmbed ONNX files" | |
| requires-python = ">=3.11,<3.13" | |
| dependencies = [ | |
| "onnxruntime==1.31.1", | |
| "huggingface-hub>=1.0", | |
| "numpy>=2", | |
| "sentence-transformers>=6.1", | |
| "librosa>=0.11", | |
| "pyarrow>=20", | |
| "pandas>=3.1.1", | |
| "tqdm", | |
| "pillow>=11", | |
| "torchvision>=0.23", | |
| ] | |