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.
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.
🗣️ 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
🗣️ 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
It has an estimated ELO of ~1400... can you beat it? 👀
(runs on both mobile and desktop)
It has an estimated ELO of ~1400... can you beat it? 👀
(runs on both mobile and desktop)
Generate 10 seconds of speech in ~1 second for $0.
What will you build? 🔥
Generate 10 seconds of speech in ~1 second for $0.
What will you build? 🔥
Link to models/samples: huggingface.co/onnx-communi...
Link to models/samples: huggingface.co/onnx-communi...
👉 npm i kokoro-js 👈
Link to demo (+ sample code) in 🧵
👉 npm i kokoro-js 👈
Link to demo (+ sample code) in 🧵
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 🧵👇
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 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! 🦙
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! 🦙
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! 👇
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! 👇
🚀 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! 👇
🚀 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! 👇
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 👇
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 👇
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...
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...
Powered by 🤗 Transformers.js and ONNX Runtime Web!
How many tokens/second do you get? Let me know! 👇
Powered by 🤗 Transformers.js and ONNX Runtime Web!
How many tokens/second do you get? Let me know! 👇
⚡ WebGPU support (up to 100x faster than WASM)
🔢 New quantization formats
🏛 121 supported architectures in total
🤖 Over 1200 pre-converted models
Get started with `npm i @huggingface/transformers`
⚡ WebGPU support (up to 100x faster than WASM)
🔢 New quantization formats
🏛 121 supported architectures in total
🤖 Over 1200 pre-converted models
Get started with `npm i @huggingface/transformers`