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...
SkillScore100Maintained
Automatic
◆AI Engineer pack
Last verified 8/11/2026
What it changes
Passed 22 of 22 test cases with the skill, and 12 of 22 without it.
Without skill55%
With skill100%
Checks it passed that the model alone missed
The code uses the ModelRegistry class.
The code instantiates the Tokenizer class.
The pipeline task specified is text-generation.
and 11 more in the full report
10 fixed12 passed either way0 still failing0 broke
Pass-rate lift
+45 pp
Tokens
+219%
Agent turns
0%
Response time
-48%
Model gemini-3.6-flashMeasured 8/11/2026v122 of 22 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 10
Prompt
Before deciding whether to download full precision or quantized ONNX binaries for a specific model ID, we want to query the registry to check which precision formats exist for that repository. What static registry method provides this list?
What was checked, without and with the skill
Checked
Without skill
With skill
The code calls ModelRegistry.get_available_dtypes.
Missed
Passed
case-19 · gemini-3.6-flash · 8/11/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md686 lines8 files
Transformers.js - Machine Learning for JavaScript
Transformers.js enables running state-of-the-art machine learning models directly in JavaScript across browsers and server-side runtimes (Node.js, Bun, Deno), with no Python 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
npm install @huggingface/transformers
Browser Usage (CDN)
<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:
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!');