1
Pyodide + Transformers
Shares tags: deploy, self-hosted, browser/webassembly
AI Tool
Transformers.js
Bring Hugging Face models to life with pure JavaScript in the browser.
Visit Transformers.js→
DeploySelf-hostedBrowser/WebAssembly
1Experience lightning-fast ML inference with advanced GPU acceleration via WebGPU for seamless performance.
2Access over 1,200 models and 120+ architectures directly in your browser, expanding possibilities for text, vision, audio, and more.
3Deploy privacy-preserving AI applications without server costs and benefit from improved loading times with binary quantization.
overview
Overview
Transformers.js enables developers to leverage state-of-the-art AI models without relying on backend servers. With support for Hugging Face models compiled to WebAssembly/WebGPU, you can run powerful ML tasks directly in the browser.
- 1Pure JavaScript inference for easy integration.
- 2No server needed; run models on-device.
- 3Designed for modern web applications.
features
Powerful Features
Transformers.js combines cutting-edge technology to enhance your web applications. Benefit from broad compatibility with the Hugging Face Python library and advanced model architectures.
- 1Support for new models including Voxtral and NeoBERT.
- 2Flexible quantization options for resource optimization.
- 3Real-time interactivity for modern web experiences.
use cases
Use Cases
Transformers.js empowers developers across various domains to create innovative browser-based applications. From interactive chatbots to real-time image processing, the possibilities are endless.
- 1AI-powered applications for web development.
- 2Privacy-focused solutions without server costs.
- 3Seamless integration into existing projects.
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Frequently Asked Questions
+What types of models can I use with Transformers.js?
You can access over 1,200 models including text, vision, audio, and multimodal architectures such as Voxtral, LFM2, and ModernBERT.
+Do I need a backend server to use Transformers.js?
No! Transformers.js is designed for on-device inference, allowing you to run models directly in the browser without any server infrastructure.
+How does binary quantization improve performance?
Binary quantization reduces the model size, leading to faster loading times and efficient performance on devices with limited resources.