A screenshot of a YouTube video titled “Intro to Transformers.js” from The Coding Train channel.
As someone who learnt so much by watching @shiffman.lol's coding videos in high school, I never imagined that one day my own library would feature on his channel! 🥹
If you're interested in learning more about 🤗 Transformers.js, I highly recommend checking it out!
👉 www.youtube.com/watch?v=KR61...
As always, the demo is open source (which you can find under the "Files" tab), so I'm excited to see how the community builds upon this! 🚀
🔗 Link to demo: huggingface.co/spaces/Liqui...
The next generation of AI-powered websites is going to be WILD! 🤯
In-browser tool calling & MCP is finally here, allowing LLMs to interact with websites programmatically.
To show what's possible, I built a demo using Liquid AI's new LFM2 model, powered by 🤗 Transformers.js.
That's right, we're running Mistral's new Voxtral-Mini-3B model 100% locally in-browser on WebGPU, powered by Transformers.js and ONNX Runtime Web! 🔥
Try it out yourself! 👇
huggingface.co/spaces/webml...
Introducing Voxtral WebGPU: State-of-the-art audio transcription directly in your browser! 🤯
🗣️ Transcribe videos, meeting notes, songs and more
🔐 Runs on-device, meaning no data is sent to a server
🌎 Multilingual (8 languages)
🤗 Completely free (forever) & open source
A community member trained a tiny Llama model (23M parameters) on 3 million high-quality @lichess.org games, then deployed it to run entirely in-browser with 🤗 Transformers.js! Super cool! 🔥
It has an estimated ELO of ~1400... can you beat it? 👀
(runs on both mobile and desktop)
The most difficult part was getting the model running in the first place, but the next steps are simple:
✂️ Implement sentence splitting, enabling streamed responses
🌍 Multilingual support (only phonemization left)
Who wants to help? 🤗
huggingface.co/spaces/webml...
We did it! Kokoro TTS (v1.0) can now run 100% locally in your browser w/ WebGPU acceleration. Real-time text-to-speech without a server. ⚡️
Generate 10 seconds of speech in ~1 second for $0.
What will you build? 🔥
The model is also extremely resilient to quantization. The smallest variant is only 86 MB in size (down from the original 326 MB), with no noticeable difference in audio quality! 🤯
Link to models/samples: huggingface.co/onnx-communi...
import { KokoroTTS } from "kokoro-js"; const tts = await KokoroTTS.from_pretrained( "onnx-community/Kokoro-82M-ONNX", { dtype: "q8" }, // fp32, fp16, q8, q4, q4f16 ); const text = "Life is like a box of chocolates. You never know what you're gonna get."; const audio = await tts.generate(text, { voice: "af_sky" }, // See `tts.list_voices()` ); audio.save("audio.wav");
You can get started in just a few lines of code! 🧑💻
Huge kudos to the Kokoro TTS community, especially taylorchu for the ONNX exports and Hexgrad for the amazing project! None of this would be possible without you all! 🤗
Try it out yourself: huggingface.co/spaces/webml...
Introducing Kokoro.js, a new JavaScript library for running Kokoro TTS, an 82 million parameter text-to-speech model, 100% locally in the browser w/ WASM. Powered by 🤗 Transformers.js. WebGPU support coming soon!
👉 npm i kokoro-js 👈
Link to demo (+ sample code) in 🧵
For the AI builders out there: imagine what could be achieved with a browser extension that (1) uses a powerful reasoning LLM, (2) runs 100% locally & privately, and (3) can directly access/manipulate the DOM! 👀
💻 Source code: github.com/huggingface/...
🔗 Online demo: huggingface.co/spaces/webml...
Is this the future of AI browser agents? 👀 WebGPU-accelerated reasoning LLMs are now supported in Transformers.js! 🤯
Here's MiniThinky-v2 (1B) running 100% locally in the browser at ~60 tps (no API calls)! I can't wait to see what you build with it!
Demo + source code in 🧵👇
This project was greatly inspired by Brendan Bycroft's amazing LLM Visualization tool – check it out if you haven't already! Also, thanks to Niels Rogge for adding DINOv2 w/ Registers to transformers! 🤗
Source code: github.com/huggingface/...
Online demo: huggingface.co/spaces/webml...
Another interesting thing to see is how the attention maps become far more refined in later layers of the transformer. For example,
First layer (1) – noisy and diffuse, capturing broad general patterns.
Last layer (12) – focused and precise, highlighting specific features.
Vision Transformers work by dividing images into fixed-size patches (e.g., 14 × 14), flattening each patch into a vector and treating each as a token.
It's fascinating to see what each attention head learns to "focus on". For example, layer 11, head 1 seems to identify eyes. Spooky! 👀
The app loads a small DINOv2 model into the user's browser and runs it locally using Transformers.js! 🤗
This means you can analyze your own images for free: simply click the image to open the file dialog.
E.g., the model recognizes that long necks and fluffy ears are defining features of llamas! 🦙
First project of 2025: Vision Transformer Explorer
I built a web app to interactively explore the self-attention maps produced by ViTs. This explains what the model is focusing on when making predictions, and provides insights into its inner workings! 🤯
Try it out yourself! 👇
Yeah, I ran into this during development, and is unfortunately a bug in Firefox:
- bugzilla.mozilla.org/show_bug.cgi...
- bugzilla.mozilla.org/show_bug.cgi...
Huge shout-out to the Useful Sensors team for such an amazing model and to Wael Yasmina for his 3D audio visualizer tutorial! 🤗
💻 Source code: github.com/huggingface/...
🔗 Online demo: huggingface.co/spaces/webml...
Introducing Moonshine Web: real-time speech recognition running 100% locally in your browser!
🚀 Faster and more accurate than Whisper
🔒 Privacy-focused (no data leaves your device)
⚡️ WebGPU accelerated (w/ WASM fallback)
🔥 Powered by ONNX Runtime Web and Transformers.js
Demo + source code below! 👇
🤗NEW PIECE:
‘Open-source’ is becoming a buzzword for many aspects of modern journalism, including open-source AI. But what is it, and how can journalists benefit from it?
@marinaadami.bsky.social spoke to @fdaudens.bsky.social to find out.
reutersinstitute.politics.ox.ac.uk/news/journal...
Huge shout-out to OuteAI for their amazing model (OuteTTS-0.2-500M) and for helping us bring it to the web! 🤗 Together, we released the outetts NPM package, which you can install with `npm i outetts`.
💻 Source code: github.com/huggingface/...
🔗 Demo: huggingface.co/spaces/webml...
The model is multilingual (English, Chinese, Korean & Japanese) and even supports zero-shot voice cloning! 🤯 Stay tuned for an update that will add these features to the UI!
More samples:
bsky.app/profile/reac...
Introducing TTS WebGPU: The first ever text-to-speech web app built with WebGPU acceleration! 🔥
High-quality and natural speech generation that runs 100% locally in your browser, powered by OuteTTS and Transformers.js. 🤗 Try it out yourself!
Demo + source code below 👇
6. MGP-STR for optical character recognition (OCR)
7. PatchTST & PatchTSMixer for time series forecasting
That's right, everything running 100% locally in your browser (no data sent to a server)! 🔥 Huge for privacy!
Check out the release notes for more information. 👇
github.com/huggingface/...
2. Qwen2-VL from Qwen for dynamic-resolution image understanding
3. JinaCLIP from Jina AI for general-purpose multilingual multimodal embeddings
4. LLaVA-OneVision from ByteDance for Image-Text-to-Text generation
5. ViTPose for pose estimation
We just released Transformers.js v3.1 and you're not going to believe what's now possible in the browser w/ WebGPU! 🤯 Let's take a look:
1. Janus from Deepseek for unified multimodal understanding and generation (Text-to-Image and Image-Text-to-Text)
Demo (+ source code): hf.co/spaces/webml...
