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Adina Yakefu

AdinaY
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reacted to fdaudens's post with 🔥 about 2 hours ago
What if AI becomes as ubiquitous as the internet, but runs locally and transparently on our devices? Fascinating TED talk by @thomwolf on open source AI and its future impact. Imagine this for AI: instead of black box models running in distant data centers, we get transparent AI that runs locally on our phones and laptops, often without needing internet access. If the original team moves on? No problem - resilience is one of the beauties of open source. Anyone (companies, collectives, or individuals) can adapt and fix these models. This is a compelling vision of AI's future that solves many of today's concerns around AI transparency and centralized control. Watch the full talk here: https://www.ted.com/talks/thomas_wolf_what_if_ai_just_works
updated a collection about 3 hours ago
2025 February
liked a model about 3 hours ago
qihoo360/TinyR1-32B-Preview
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AdinaY's activity

reacted to fdaudens's post with 🔥 about 2 hours ago
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187
What if AI becomes as ubiquitous as the internet, but runs locally and transparently on our devices?

Fascinating TED talk by @thomwolf on open source AI and its future impact.

Imagine this for AI: instead of black box models running in distant data centers, we get transparent AI that runs locally on our phones and laptops, often without needing internet access. If the original team moves on? No problem - resilience is one of the beauties of open source. Anyone (companies, collectives, or individuals) can adapt and fix these models.

This is a compelling vision of AI's future that solves many of today's concerns around AI transparency and centralized control.

Watch the full talk here: https://www.ted.com/talks/thomas_wolf_what_if_ai_just_works
posted an update about 4 hours ago
posted an update about 4 hours ago
reacted to burtenshaw's post with 🔥 2 days ago
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5405
Now the Hugging Face agent course is getting real! With frameworks like smolagents, LlamaIndex, and LangChain.

🔗 Follow the org for updates https://huggingface.co./agents-course

This week we are releasing the first framework unit in the course and it’s on smolagents. This is what the unit covers:

- why should you use smolagents vs another library?
- how to build agents that use code
- build multiagents systems
- use vision language models for browser use

The team has been working flat out on this for a few weeks. Led by @sergiopaniego and supported by smolagents author @m-ric .
reacted to freddyaboulton's post with 🔥🚀 2 days ago
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2820
Getting WebRTC and Websockets right in python is very tricky. If you've tried to wrap an LLM in a real-time audio layer then you know what I'm talking about.

That's where FastRTC comes in! It makes WebRTC and Websocket streams super easy with minimal code and overhead.

Check out our org: hf.co/fastrtc
posted an update 3 days ago
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2578
Wan2.1 🔥📹 new OPEN video model by Alibaba Wan team!

Model: Wan-AI/Wan2.1-T2V-14B
Demo: Wan-AI/Wan2.1

✨Apache 2.0
✨8.19GB VRAM, runs on most GPUs
✨Multi-Tasking: T2V, I2V, Video Editing, T2I, V2A
✨Text Generation: Supports Chinese & English
✨Powerful Video VAE: Encode/decode 1080P w/ temporal precision
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posted an update 4 days ago
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2824
Try QwQ-Max-Preview, Qwen's reasoning model here👉 https://chat.qwen.ai
Can't wait for the model weights to drop on the Hugging Face Hub 🔥
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reacted to fdaudens's post with ❤️ 4 days ago
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3162
🚀 Just launched: A toolkit of 20 powerful AI tools that journalists can use right now - transcribe, analyze, create. 100% free & open-source.

Been testing all these tools myself and created a searchable collection of the most practical ones - from audio transcription to image generation to document analysis. No coding needed, no expensive subscriptions.

Some highlights I've tested personally:
- Private, on-device transcription with speaker ID in 100+ languages using Whisper
- Website scraping that just works - paste a URL, get structured data
- Local image editing with tools like Finegrain (impressive results)
- Document chat using Qwen 2.5 72B (handles technical papers well)

Sharing this early because the best tools come from the community. Drop your favorite tools in the comments or join the discussion on what to add next!

👉 JournalistsonHF/ai-toolkit
reacted to their post with 🔥 4 days ago
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2396
Two AI startups, DeepSeek & Moonshot AI , keep moving in perfect sync 👇

✨ Last December: DeepSeek & Moonshot AI released their reasoning models on the SAME DAY.
DeepSeek: deepseek-ai/DeepSeek-R1
MoonShot: https://github.com/MoonshotAI/Kimi-k1.5

✨ Last week: Both teams published papers on modifying attention mechanisms on the SAME DAY AGAIN.
DeepSeek: Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention (2502.11089)
Moonshot: MoBA: Mixture of Block Attention for Long-Context LLMs (2502.13189)

✨ TODAY:
DeepSeek unveiled Flash MLA: a efficient MLA decoding kernel for NVIDIA Hopper GPUs, optimized for variable-length sequences.
https://github.com/deepseek-ai/FlashMLA

Moonshot AI introduces Moonlight: a 3B/16B MoE trained on 5.7T tokens using Muon, pushing the Pareto frontier with fewer FLOPs.
moonshotai/Moonlight-16B-A3B

What's next? 👀
posted an update 4 days ago
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2396
Two AI startups, DeepSeek & Moonshot AI , keep moving in perfect sync 👇

✨ Last December: DeepSeek & Moonshot AI released their reasoning models on the SAME DAY.
DeepSeek: deepseek-ai/DeepSeek-R1
MoonShot: https://github.com/MoonshotAI/Kimi-k1.5

✨ Last week: Both teams published papers on modifying attention mechanisms on the SAME DAY AGAIN.
DeepSeek: Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention (2502.11089)
Moonshot: MoBA: Mixture of Block Attention for Long-Context LLMs (2502.13189)

✨ TODAY:
DeepSeek unveiled Flash MLA: a efficient MLA decoding kernel for NVIDIA Hopper GPUs, optimized for variable-length sequences.
https://github.com/deepseek-ai/FlashMLA

Moonshot AI introduces Moonlight: a 3B/16B MoE trained on 5.7T tokens using Muon, pushing the Pareto frontier with fewer FLOPs.
moonshotai/Moonlight-16B-A3B

What's next? 👀
posted an update 8 days ago
reacted to clem's post with ❤️🔥 9 days ago
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3413
We crossed 1B+ tokens routed to inference providers partners on HF, that we released just a few days ago.

Just getting started of course but early users seem to like it & always happy to be able to partner with cool startups in the ecosystem.

Have you been using any integration and how can we make it better?

https://huggingface.co./blog/inference-providers
reacted to ginipick's post with 🚀🔥 9 days ago
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5852
🚀 FLUX Workflow Canvas

Welcome to Workflow Canvas, your ultimate AI-driven platform for crafting stunning design concepts and intricate workflow diagrams that empower your business! 🤖✨

ginigen/Workflow-Canvas

Features
Product Design 🛠️
Transform your ideas into reality with sleek, industrial product designs that blend modern aesthetics with advanced technology.

Mindmap 🧠
Generate vibrant, educational mind maps that outline your strategies and processes in a clear, visually engaging layout.

Mockup 📱
Quickly prototype intuitive app interfaces and web designs using clean, hand-drawn wireframes that capture your vision.

Infographic 📊
Build polished, data-rich infographics that communicate complex corporate metrics and trends with style and clarity.

Diagram 📈
Illustrate comprehensive, end-to-end business workflows—from market analysis to implementation—with detailed and organized diagrams.

Flowchart 🔄
Design easy-to-follow, hand-drawn style flowcharts that map out your operational processes using vibrant colors and minimalistic icons.

How It Works
Set Your Parameters:
Customize your creative process by adjusting the seed, dimensions, inference steps, and guidance scale through the intuitive sidebar.

Choose Your Visual Style:
Explore our diverse range of tabs—from Product Design and Mindmap to Flowchart—each tailored to a unique creative output.

Get Inspired:
Dive into our rich library of example prompts featuring detailed lists and tree structures to instantly populate your design ideas.

Generate Your Masterpiece:
Click the “Generate” button and watch as your ideas come to life in beautifully rendered images! 🎨

Experience the fusion of art and technology with Workflow Canvas – where your business ideas transform into dynamic, visual masterpieces. Get started today and revolutionize the way you design! 🚀
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reacted to m-ric's post with 👍🚀 9 days ago
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2909
Less is More for Reasoning (LIMO): a 32B model fine-tuned with 817 examples can beat o1-preview on math reasoning! 🤯

Do we really need o1's huge RL procedure to see reasoning emerge? It seems not.
Researchers from Shanghai Jiaotong University just demonstrated that carefully selected examples can boost math performance in large language models using SFT —no huge datasets or RL procedures needed.

Their procedure allows Qwen2.5-32B-Instruct to jump from 6.5% to 57% on AIME and from 59% to 95% on MATH, while using only 1% of the data in previous approaches.

⚡ The Less-is-More Reasoning Hypothesis:
‣ Minimal but precise examples that showcase optimal reasoning patterns matter more than sheer quantity
‣ Pre-training knowledge plus sufficient computational resources at inference levels up math skills

➡️ Core techniques:
‣ High-quality reasoning chains with self-verification steps
‣ 817 handpicked problems that encourage deeper reasoning
‣ Enough inference-time computation to allow extended reasoning

💪 Efficiency gains:
‣ Only 817 examples instead of 100k+
‣ 40.5% absolute improvement across 10 diverse benchmarks, outperforming models trained on 100x more data

This really challenges the notion that SFT leads to memorization rather than generalization! And opens up reasoning to GPU-poor researchers 🚀

Read the full paper here 👉  LIMO: Less is More for Reasoning (2502.03387)
posted an update 10 days ago
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4179
🚀 StepFun阶跃星辰 is making BIG open moves!

Last year, their GOT-OCR 2.0 took the community by storm 🔥but many didn’t know they were also building some amazing models. Now, they’ve just dropped something huge on the hub!

📺 Step-Video-T2V: a 30B bilingual open video model that generates 204 frames (8-10s) at 540P resolution with high information density & consistency.
stepfun-ai/stepvideo-t2v

🔊 Step-Audio-TTS-3B : a TTS trained with the LLM-Chat paradigm on a large synthetic dataset, capable of generating RAP & Humming
stepfun-ai/step-audio-67b33accf45735bb21131b0b
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posted an update 10 days ago