SKILL.md
---
source: "https://github.com/huggingface/skills/tree/main/skills/transformers-js"
name: transformers-js
description: Run Hugging Face models in JavaScript or TypeScript with Transformers.js in Node.js or the browser.
license: Apache-2.0
risk: unknown
metadata:
author: huggingface
version: "3.8.1"
category: machine-learning
repository: https://github.com/huggingface/transformers.js
compatibility: Requires Node.js 18+ or modern browser with ES modules support. WebGPU support requires compatible browser/environment. Internet access needed for downloading models from Hugging Face Hub (optional if using local models).
---
# Transformers.js - Machine Learning for JavaScript
Transformers.js enables running state-of-the-art machine learning models directly in JavaScript, both in browsers and Node.js environments, with no server required.
## When to Use This Skill
Use this skill when you need to:
- Run ML models for text analysis, generation, or translation in JavaScript
- Perform image classification, object detection, or segmentation
- Implement speech recognition or audio processing
- Build multimodal AI applications (text-to-image, image-to-text, etc.)
- Run models client-side in the browser without a backend
## Installation
### NPM Installation
```bash
npm install @huggingface/transformers
```
### Browser Usage (CDN)
```javascript
<script type="module">
import { pipeline } from 'https://cdn.jsdelivr.net/npm/@huggingface/transformers';
</script>
```
## Core Concepts
### 1. Pipeline API
The pipeline API is the easiest way to use models. It groups together preprocessing, model inference, and postprocessing:
```javascript
import { pipeline } from '@huggingface/transformers';
// Create a pipeline for a specific task
const pipe = await pipeline('sentiment-analysis');
// Use the pipeline
const result = await pipe('I love transformers!');
// Output: [{ label: 'POSITIVE', score: 0.999817686 }]
// IMPORTANT: Always dispose when done to free memory
await