Instructions to use Xenova/tiny-random-vits with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use Xenova/tiny-random-vits with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-to-speech', 'Xenova/tiny-random-vits');
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Download README.md from Xenova/tiny-random-vits: direct link, hf CLI and curl.
- Browser
- Download file 596 Bytes
-
https://huggingface.co/Xenova/tiny-random-vits/resolve/main/README.md
- Command line
-
hf download hf://Xenova/tiny-random-vits/README.md
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curl -L -o README.md https://huggingface.co/Xenova/tiny-random-vits/resolve/main/README.md
596 Bytes
metadata
base_model: echarlaix/tiny-random-vits
library_name: transformers.js
pipeline_tag: text-to-speech
tags:
- text-to-audio
https://huggingface.co/echarlaix/tiny-random-vits with ONNX weights to be compatible with Transformers.js.
Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using 🤗 Optimum and structuring your repo like this one (with ONNX weights located in a subfolder named onnx).