# transformers.js

JavaScript library for running Hugging Face Transformer models in web browsers and other JavaScript environments.

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## Run AI in the Browser: A Practical Guide to Transformers.js

DevFeed: [Run AI in the Browser: A Practical Guide to Transformers.js](<https://devfeed.tech/articles/run-ai-in-the-browser-a-practical-guide-to-transformers-js-33301.md>)

Original publisher: [Read original article](<https://freek.dev/3188-run-ai-in-the-browser-a-practical-guide-to-transformersjs>)

Author: Freek Van der Herten (freek@spatie.be)

Published: 2026-09-09T14:50:26Z

Content type: tutorial

Language: en

Sources: [freek.dev - all blogposts](<https://devfeed.tech/sources/freek-dev-all-blogposts.md>)

Topics: [transformers.js](<https://devfeed.tech/topics/transformers-js.md>), [browser](<https://devfeed.tech/topics/browser.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [AI Models](<https://devfeed.tech/topics/ai-models.md>), [Back end](<https://devfeed.tech/topics/backend.md>), [API keys](<https://devfeed.tech/topics/api-keys.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [ai-models](<https://devfeed.tech/tags/ai-models.md>), [api-keys](<https://devfeed.tech/tags/api-keys.md>), [article](<https://devfeed.tech/tags/article.md>), [backend](<https://devfeed.tech/tags/backend.md>), [browser](<https://devfeed.tech/tags/browser.md>), [guide](<https://devfeed.tech/tags/guide.md>), [internet](<https://devfeed.tech/tags/internet.md>), [javascript](<https://devfeed.tech/tags/javascript.md>), [js](<https://devfeed.tech/tags/js.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [practical](<https://devfeed.tech/tags/practical.md>), [run](<https://devfeed.tech/tags/run.md>), [transformers](<https://devfeed.tech/tags/transformers.md>), [transformers-js](<https://devfeed.tech/tags/transformers-js.md>)

### AI overview

A practical guide to Transformers.js, covering how it runs AI models directly in the browser, available models, and the trade-offs of client-side AI compared with traditional AI providers.

### Source excerpt

Transformers.js lets you run AI models directly in the browser without a backend, API keys, or an internet connection after the model is cached. The article explores how it works, which models are available, and the trade-offs of client-side AI compared to traditional AI providers. Read more

## How to Use Transformers.js in a Chrome Extension

DevFeed: [How to Use Transformers.js in a Chrome Extension](<https://devfeed.tech/articles/how-to-use-transformers-js-in-a-chrome-extension-7538.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/transformersjs-chrome-extension>)

Author: Nico Martin

Published: 2026-04-23T00:00:00Z

Content type: tutorial

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [Chrome extension](<https://devfeed.tech/topics/chrome-extension.md>), [transformers.js](<https://devfeed.tech/topics/transformers-js.md>), [gemma4](<https://devfeed.tech/topics/gemma4.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Local AI](<https://devfeed.tech/topics/local-ai.md>), [Open Source](<https://devfeed.tech/topics/open-source.md>), [Code](<https://devfeed.tech/topics/code.md>)

Tags: [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [chrome](<https://devfeed.tech/tags/chrome.md>), [chrome-extension](<https://devfeed.tech/tags/chrome-extension.md>), [code](<https://devfeed.tech/tags/code.md>), [extension](<https://devfeed.tech/tags/extension.md>), [github](<https://devfeed.tech/tags/github.md>), [guide](<https://devfeed.tech/tags/guide.md>), [inference](<https://devfeed.tech/tags/inference.md>), [javascript](<https://devfeed.tech/tags/javascript.md>), [local](<https://devfeed.tech/tags/local.md>), [local-ai](<https://devfeed.tech/tags/local-ai.md>), [manifest](<https://devfeed.tech/tags/manifest.md>), [on-device](<https://devfeed.tech/tags/on-device.md>), [open](<https://devfeed.tech/tags/open.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [transformers](<https://devfeed.tech/tags/transformers.md>), [transformers-js](<https://devfeed.tech/tags/transformers-js.md>), [ui](<https://devfeed.tech/tags/ui.md>), [web](<https://devfeed.tech/tags/web.md>)

### AI overview

A developer guide to building a local AI Chrome extension with Transformers.js under Manifest V3. It explains an architecture with a background service worker hosting models, a side-panel chat interface, and a content script for page extraction and highlighting, using the Gemma 4 Browser Assistant as a reference.

### Source excerpt

We're on a journey to advance and democratize artificial intelligence through open source and open science.

## Transformers.js v4: Now Available on NPM!

DevFeed: [Transformers.js v4: Now Available on NPM!](<https://devfeed.tech/articles/transformers-js-v4-now-available-on-npm-7540.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/transformersjs-v4>)

Author: Joshua; Nico Martin

Published: 2026-02-09T00:00:00Z

Content type: release

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [transformers.js](<https://devfeed.tech/topics/transformers-js.md>), [webgpu](<https://devfeed.tech/topics/webgpu.md>), [JavaScript](<https://devfeed.tech/topics/javascript.md>), [AI Models](<https://devfeed.tech/topics/ai-models.md>), [AI Inference](<https://devfeed.tech/topics/ai-inference.md>), [Refactoring](<https://devfeed.tech/topics/refactoring.md>), [npm](<https://devfeed.tech/topics/npm.md>), [Open Source](<https://devfeed.tech/topics/open-source.md>), [Bun](<https://devfeed.tech/topics/bun.md>), [Deno](<https://devfeed.tech/topics/deno.md>)

Tags: [ai-models](<https://devfeed.tech/tags/ai-models.md>), [announcement](<https://devfeed.tech/tags/announcement.md>), [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [code](<https://devfeed.tech/tags/code.md>), [javascript](<https://devfeed.tech/tags/javascript.md>), [language-models](<https://devfeed.tech/tags/language-models.md>), [large-language-models](<https://devfeed.tech/tags/large-language-models.md>), [model](<https://devfeed.tech/tags/model.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [refactoring](<https://devfeed.tech/tags/refactoring.md>), [transformers](<https://devfeed.tech/tags/transformers.md>), [transformers-js](<https://devfeed.tech/tags/transformers-js.md>), [webgpu](<https://devfeed.tech/tags/webgpu.md>)

### AI overview

Transformers.js v4 introduces a C++-rewritten WebGPU runtime with broader operator support and shared execution across browsers, servers, Node, Bun, and Deno. The release also improves local AI model performance through ONNX Runtime operators, reorganizes the project as a pnpm monorepo, and splits model definitions into focused modules.

### Source excerpt

We're on a journey to advance and democratize artificial intelligence through open source and open science.

## Welcome EmbeddingGemma, Google's new efficient embedding model

DevFeed: [Welcome EmbeddingGemma, Google's new efficient embedding model](<https://devfeed.tech/articles/welcome-embeddinggemma-google-s-new-efficient-embedding-model-7180.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/embeddinggemma>)

Author: Tom Aarsen; Joshua; Alvaro Bartolome; Aritra Roy Gosthipaty; Pedro Cuenca; Sergio Paniego

Published: 2025-09-04T00:00:00Z

Content type: article

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [Embeddings](<https://devfeed.tech/topics/embeddings.md>), [sentence-transformers](<https://devfeed.tech/topics/sentence-transformers.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Google](<https://devfeed.tech/topics/google.md>), [Retrieval-Augmented Generation](<https://devfeed.tech/topics/retrieval-augmented-generation.md>), [Open Source](<https://devfeed.tech/topics/open-source.md>), [transformers.js](<https://devfeed.tech/topics/transformers-js.md>), [Inference](<https://devfeed.tech/topics/inference.md>), [onnx](<https://devfeed.tech/topics/onnx.md>), [dataset](<https://devfeed.tech/topics/dataset.md>), [LangChain](<https://devfeed.tech/topics/langchain.md>), [llamaindex](<https://devfeed.tech/topics/llamaindex.md>)

Tags: [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [benchmark](<https://devfeed.tech/tags/benchmark.md>), [community](<https://devfeed.tech/tags/community.md>), [embedding](<https://devfeed.tech/tags/embedding.md>), [google](<https://devfeed.tech/tags/google.md>), [guide](<https://devfeed.tech/tags/guide.md>), [langchain](<https://devfeed.tech/tags/langchain.md>), [llamaindex](<https://devfeed.tech/tags/llamaindex.md>), [nlp](<https://devfeed.tech/tags/nlp.md>), [on-device](<https://devfeed.tech/tags/on-device.md>), [onnx](<https://devfeed.tech/tags/onnx.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [rag](<https://devfeed.tech/tags/rag.md>), [sentence-transformers](<https://devfeed.tech/tags/sentence-transformers.md>), [transformers-js](<https://devfeed.tech/tags/transformers-js.md>)

### AI overview

Google introduces EmbeddingGemma, a compact multilingual embedding model designed for fast, efficient on-device use. The article covers its architecture, training, multilingual capabilities, benchmark performance, framework integrations, and domain fine-tuning for retrieval applications.

### Source excerpt

We're on a journey to advance and democratize artificial intelligence through open source and open science.

## Gemma 3n fully available in the open-source ecosystem!

DevFeed: [Gemma 3n fully available in the open-source ecosystem!](<https://devfeed.tech/articles/gemma-3n-fully-available-in-the-open-source-ecosystem-7213.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/gemma3n>)

Author: Aritra Roy Gosthipaty; Pedro Cuenca; Sergio Paniego; Vaibhav Srivastav; Christopher Fleetwood; Joshua; Steven Zheng; Kashif Rasul

Published: 2025-06-26T00:00:00Z

Content type: article

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [gemma](<https://devfeed.tech/topics/gemma.md>), [Open Source](<https://devfeed.tech/topics/open-source.md>), [AI Development](<https://devfeed.tech/topics/ai-development.md>), [llama.cpp](<https://devfeed.tech/topics/llama-cpp.md>), [MLX](<https://devfeed.tech/topics/mlx.md>), [Ollama](<https://devfeed.tech/topics/ollama.md>), [transformers.js](<https://devfeed.tech/topics/transformers-js.md>), [GPU](<https://devfeed.tech/topics/gpu.md>), [Hardware](<https://devfeed.tech/topics/hardware.md>), [timm](<https://devfeed.tech/topics/timm.md>), [asr](<https://devfeed.tech/topics/asr.md>), [Embeddings](<https://devfeed.tech/topics/embeddings.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [audio](<https://devfeed.tech/tags/audio.md>), [community](<https://devfeed.tech/tags/community.md>), [embeddings](<https://devfeed.tech/tags/embeddings.md>), [gemma](<https://devfeed.tech/tags/gemma.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [hardware](<https://devfeed.tech/tags/hardware.md>), [implementation](<https://devfeed.tech/tags/implementation.md>), [llama-cpp](<https://devfeed.tech/tags/llama-cpp.md>), [llm](<https://devfeed.tech/tags/llm.md>), [mlx](<https://devfeed.tech/tags/mlx.md>), [multimodal](<https://devfeed.tech/tags/multimodal.md>), [ollama](<https://devfeed.tech/tags/ollama.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [release](<https://devfeed.tech/tags/release.md>), [research](<https://devfeed.tech/tags/research.md>), [speech](<https://devfeed.tech/tags/speech.md>), [timm](<https://devfeed.tech/tags/timm.md>), [transformers](<https://devfeed.tech/tags/transformers.md>), [transformers-js](<https://devfeed.tech/tags/transformers-js.md>), [translation](<https://devfeed.tech/tags/translation.md>), [vision](<https://devfeed.tech/tags/vision.md>), [vlm](<https://devfeed.tech/tags/vlm.md>)

### AI overview

This article announces the availability of Gemma 3n in major open-source libraries and presents practical usage and fine-tuning examples. It describes the model variants, memory-efficient hardware requirements, multimodal audio and vision encoders, speech-to-text and translation capabilities, and architectural features including MatFormer and Per-Layer Embeddings.

### Source excerpt

We're on a journey to advance and democratize artificial intelligence through open source and open science.

## Transformers.js v3: WebGPU Support, New Models & Tasks, and More...

DevFeed: [Transformers.js v3: WebGPU Support, New Models & Tasks, and More...](<https://devfeed.tech/articles/transformers-js-v3-webgpu-support-new-models-tasks-and-more-7539.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/transformersjs-v3>)

Author: Joshua

Published: 2024-10-22T00:00:00Z

Content type: article

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [transformers.js](<https://devfeed.tech/topics/transformers-js.md>), [webgpu](<https://devfeed.tech/topics/webgpu.md>), [AI Inference](<https://devfeed.tech/topics/ai-inference.md>), [quantization](<https://devfeed.tech/topics/quantization.md>), [Whisper](<https://devfeed.tech/topics/whisper.md>), [asr](<https://devfeed.tech/topics/asr.md>)

Tags: [announcement](<https://devfeed.tech/tags/announcement.md>), [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [javascript](<https://devfeed.tech/tags/javascript.md>), [npm](<https://devfeed.tech/tags/npm.md>), [onnx](<https://devfeed.tech/tags/onnx.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [quantization](<https://devfeed.tech/tags/quantization.md>), [transformers](<https://devfeed.tech/tags/transformers.md>), [transformers-js](<https://devfeed.tech/tags/transformers-js.md>), [webgl](<https://devfeed.tech/tags/webgl.md>), [webgpu](<https://devfeed.tech/tags/webgpu.md>)

### AI overview

Transformers.js v3 adds WebGPU acceleration for browser-based machine learning, support for more quantization options and per-module data types, and 120 supported model architectures. The release includes examples for text embeddings, speech recognition with Whisper, image classification, and other models and tasks.

### Source excerpt

We're on a journey to advance and democratize artificial intelligence through open source and open science.

## In-Browser Semantic AI Search with PGlite and Transformers.js

DevFeed: [In-Browser Semantic AI Search with PGlite and Transformers.js](<https://devfeed.tech/articles/in-browser-semantic-ai-search-with-pglite-and-transformers-js-401.md>)

Original publisher: [Read original article](<https://supabase.com/blog/in-browser-semantic-search-pglite>)

Author: Thor Schaeff

Published: 2024-08-29T07:00:00Z

Content type: tutorial

Language: en

Sources: [Supabase Blog](<https://devfeed.tech/sources/supabase-blog.md>)

Topics: [AI search](<https://devfeed.tech/topics/ai-search.md>), [transformers.js](<https://devfeed.tech/topics/transformers-js.md>), [browser](<https://devfeed.tech/topics/browser.md>), [Embeddings](<https://devfeed.tech/topics/embeddings.md>), [Database](<https://devfeed.tech/topics/database.md>), [React](<https://devfeed.tech/topics/react.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [ai-search](<https://devfeed.tech/tags/ai-search.md>), [browser](<https://devfeed.tech/tags/browser.md>), [build](<https://devfeed.tech/tags/build.md>), [database](<https://devfeed.tech/tags/database.md>), [embeddings](<https://devfeed.tech/tags/embeddings.md>), [js](<https://devfeed.tech/tags/js.md>), [local](<https://devfeed.tech/tags/local.md>), [react](<https://devfeed.tech/tags/react.md>), [search](<https://devfeed.tech/tags/search.md>), [transformers](<https://devfeed.tech/tags/transformers.md>), [transformers-js](<https://devfeed.tech/tags/transformers-js.md>), [web](<https://devfeed.tech/tags/web.md>)

### AI overview

A tutorial for building fully local, in-browser semantic search with PGlite, pgvector, and Huggingface Transformers.js. It stores text and embeddings locally, generates query embeddings in a web worker, and performs inner product search without a server round trip.

### Source excerpt

Use pgvector in PGlite and combine it with Huggingface Transformers.js for a fully local, in-browser semantic search functionality!