transformers-js
Use Transformers.js to run state-of-the-art machine learning models directly in JavaScript/TypeScript. Supports NLP (text classification, translation, summarization), computer vision (image classification, object detection), audio (speech recognition, audio classification), and multimodal tasks. Works in browsers and server-side runtimes (Node.js, Bun, Deno) with WebGPU/WASM using pre-trained models from Hugging Face Hub.
Profile →npx skills add waybarrios/opencode-power-pack --skill transformers-js --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Transformers.js — Machine Learning for JavaScript Runs state-of-the-art ML models directly in JavaScript, in browsers and server-side runtimes (Node.js, Bun, Deno), with no Python server required. ## Installation ```bash npm install @huggingface/transformers ``` ```javascript // Browser (CDN) import { pipeline } from 'https://cdn.jsdelivr.net/npm/@huggingface/transformers'; ``` ## Core Concepts **Pipeline API** — groups preprocessing, inference, and postprocessing. Always `dispose()` when done to free memory (see `references/EXAMPLES.md` for cleanup patterns): ```javascript import { pipeline } from '@huggingface/transformers'; const pipe = await pipeline('sentiment-analysis'); const result = await pipe('I love transformers!'); await pipe.dispose(); ``` **Model selection** — pass a model ID as the second argument, e.g. `pipeline('sentiment-analysis', 'Xenova/bert-base-multilingual-uncased-sentiment')`. Browse compatible models at `https://huggingface.co/models?library=transformers.js&sort=trending`, filtered by `pipeline_tag` for a specific task. **Device**: `{ device: 'webgpu' }` for GPU acceleration (falls back to WASM/CPU when unsupported); omit for CPU/WASM default. **Quantiza
- Installation
- Core Concepts
- Supported Tasks
- Finding and Choosing Models
- Advanced Configuration
- Runtime Considerations
- Error Handling & Memory Management
- Troubleshooting
- Best Practices
- Resources
npm install @huggingface/transformers
What does the transformers-js skill do?
Use Transformers.js to run state-of-the-art machine learning models directly in JavaScript/TypeScript. Supports NLP (text classification, translation, summarization), computer vision (image classification, object detection), audio (speech recognition, audio classification), and multimodal tasks. Works in browsers and server-side runtimes (Node.js, Bun, Deno) with WebGPU/WASM using pre-trained models from Hugging Face Hub.
How do I install it?
Run `npx skills add waybarrios/opencode-power-pack --skill transformers-js --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From waybarrios/opencode-power-pack, a repository with 443 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.