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Optimised quants for high-throughput deployments! Compatible with Transformers, TGI & vLLM πŸ€—

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medmekkΒ  updated a model about 2 months ago
hugging-quants/Llama-4-Scout-17B-16E-Instruct-fbgemm
medmekkΒ  published a model about 2 months ago
hugging-quants/Llama-4-Scout-17B-16E-Instruct-fbgemm
medmekkΒ  updated a model about 2 months ago
hugging-quants/Llama-4-Scout-17B-16E-Instruct-fbgemm-unfused
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XenovaΒ 
posted an update 1 day ago
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818
NEW: Real-time conversational AI models can now run 100% locally in your browser! 🀯

πŸ” Privacy by design (no data leaves your device)
πŸ’° Completely free... forever
πŸ“¦ Zero installation required, just visit a website
⚑️ Blazingly-fast WebGPU-accelerated inference

Try it out: webml-community/conversational-webgpu

For those interested, here's how it works:
- Silero VAD for voice activity detection
- Whisper for speech recognition
- SmolLM2-1.7B for text generation
- Kokoro for text to speech

Powered by Transformers.js and ONNX Runtime Web! πŸ€— I hope you like it!
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danieldkΒ 
posted an update 1 day ago
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698
We have been working on a project called kernels. kernels makes it possible to load compute kernels directly from the Hub! πŸš€

We plan to give kernels a more proper introduction soon. But for those who have been following along, we are happy to announce a new release:

- New layer API with torch.compile support.
- Experimental support for loading Apple Silicon Metal 🀘 Kernels.
- Generate wheels from Hub kernels for legacy deployments.

Full release notes here: https://github.com/huggingface/kernels/releases/tag/v0.6.0
joaoganteΒ 
posted an update 16 days ago
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450
Let's go! Custom generation code has landed in transformers πŸš€

Have you designed a new cool KV cache? Maybe you're comparing new test-time compute ideas you've been researching? Have you found a way to do diffusion with existing models? You can now easily share your findings with the community with custom generation code, sharing the well-known generate interface πŸ€“

In a nutshell, we have expanded the support of custom modeling code on the Hub with *model-agnostic* custom generation code. Write for one model, reuse with any model -- hopefully, this will democratize access to new generation ideas 🫑

As a creator, you gain the ability to get your ideas in transformers with minimal effort. You'll also have access to all Hub features: a landing page for your creation, discussions, usage metrics, ... πŸ€“

πŸ’Ž Resources πŸ’Ž
- docs: https://huggingface.co/docs/transformers/generation_strategies#custom-decoding-methods
- minimal example: transformers-community/custom_generate_example
- discussion: transformers-community/support#10
reach-vbΒ 
posted an update 17 days ago
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3644
hey hey @mradermacher - VB from Hugging Face here, we'd love to onboard you over to our optimised xet backend! πŸ’₯

as you know we're in the process of upgrading our storage backend to xet (which helps us scale and offer blazingly fast upload/ download speeds too): https://huggingface.co/blog/xet-on-the-hub and now that we are certain that the backend can scale with even big models like Llama 4/ Qwen 3 - we;re moving to the next phase of inviting impactful orgs and users on the hub over as you are a big part of the open source ML community - we would love to onboard you next and create some excitement about it in the community too!

in terms of actual steps - it should be as simple as one of the org admins to join hf.co/join/xet - we'll take care of the rest.

p.s. you'd need to have a the latest hf_xet version of huggingface_hub lib but everything else should be the same: https://huggingface.co/docs/hub/storage-backends#using-xet-storage

p.p.s. this is fully backwards compatible so everything will work as it should! πŸ€—
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XenovaΒ 
posted an update about 1 month ago
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8072
Introducing the ONNX model explorer: Browse, search, and visualize neural networks directly in your browser. 🀯 A great tool for anyone studying Machine Learning! We're also releasing the entire dataset of graphs so you can use them in your own projects! πŸ€—

Check it out! πŸ‘‡
Demo: onnx-community/model-explorer
Dataset: onnx-community/model-explorer
Source code: https://github.com/xenova/model-explorer
XenovaΒ 
posted an update about 2 months ago
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Reasoning models like o3 and o4-mini are advancing faster than ever, but imagine what will be possible when they can run locally in your browser! 🀯

Well, with πŸ€— Transformers.js, you can do just that! Here's Zyphra's new ZR1 model running at over 100 tokens/second on WebGPU! ⚑️

Giving models access to browser APIs (like File System, Screen Capture, and more) could unlock an entirely new class of web experiences that are personalized, interactive, and run locally in a secure, sandboxed environment.

For now, try out the demo! πŸ‘‡
webml-community/Zyphra-ZR1-WebGPU
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medmekkΒ 
updated a model about 2 months ago
medmekkΒ 
published a model about 2 months ago
medmekkΒ 
updated a model about 2 months ago
medmekkΒ 
published a model about 2 months ago
pcuenqΒ 
authored a paper about 2 months ago
XenovaΒ 
authored a paper about 2 months ago
reach-vbΒ 
authored a paper about 2 months ago
alvarobarttΒ 
posted an update 3 months ago
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3166
πŸ”₯ Agents can do anything! @microsoft Research just announced the release of Magma 8B!

Magma is a new Visual Language Model (VLM) with 8B parameters for multi-modal agents designed to handle complex interactions across virtual and real environments; and it's MIT licensed!

Magma comes with exciting new features such as:
- Introduces the Set-of-Mark and Trace-of-Mark techniques for fine-tuning
- Leverages a large amount of unlabeled video data to learn the spatial-temporal grounding and planning
- A strong generalization and ability to be fine-tuned for other agentic tasks
- SOTA in different multi-modal benchmarks spanning across UI navigation, robotics manipulation, image / video understanding and spatial understanding and reasoning
- Generates goal-driven visual plans and actions for agentic use cases

Model: microsoft/Magma-8B
Technical Report: Magma: A Foundation Model for Multimodal AI Agents (2502.13130)
XenovaΒ 
posted an update 4 months ago
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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? πŸ”₯
webml-community/kokoro-webgpu

The most difficult part was getting the model running in the first place, but the next steps are simple:
βœ‚οΈ Implement sentence splitting, allowing for streamed responses
🌍 Multilingual support (only phonemization left)

Who wants to help?
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reach-vbΒ 
authored a paper 4 months ago
XenovaΒ 
authored a paper 4 months ago
XenovaΒ 
posted an update 5 months ago
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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 πŸ€— Transformers.js. WebGPU support coming soon!
πŸ‘‰ npm i kokoro-js πŸ‘ˆ

Try it out yourself: webml-community/kokoro-web
Link to models/samples: onnx-community/Kokoro-82M-ONNX

You can get started in just a few lines of code!
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");

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! πŸ€—

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! 🀯
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XenovaΒ 
posted an update 5 months ago
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8493
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! πŸ‘‡
webml-community/attention-visualization

Source code: https://github.com/huggingface/transformers.js-examples/tree/main/attention-visualization
XenovaΒ 
posted an update 6 months ago
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4436
Introducing Moonshine Web: real-time speech recognition running 100% locally in your browser!
πŸš€ Faster and more accurate than Whisper
πŸ”’ Privacy-focused (no data leaves your device)
⚑️ WebGPU accelerated (w/ WASM fallback)
πŸ”₯ Powered by ONNX Runtime Web and Transformers.js

Demo: webml-community/moonshine-web
Source code: https://github.com/huggingface/transformers.js-examples/tree/main/moonshine-web
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