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John6666

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published a model about 4 hours ago
John6666/dixar-2-double-the-dix-sdxl
published a model about 4 hours ago
John6666/phony-illustrious-mix-v10-sdxl
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John6666's activity

reacted to codelion's post with 🚀 about 7 hours ago
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834
🧠 We just implemented Andrej Karpathy's "third paradigm" for LLM learning!

System Prompt Learning (SPL) enables LLMs to automatically learn problem-solving strategies from experience, rather than relying on static prompts.

🚀 How it works:
Your LLM builds a database of effective strategies, selects the best ones for each problem, and refines them over time based on success rates.

📊 Results across math benchmarks:
Arena Hard: 29% → 37.6% (+8.6%)
AIME24: 23.33% → 30% (+6.67%)
OptILLMBench: 61% → 65% (+4%)

The best part? All strategies are human-readable and the system gets progressively better at problem types you use frequently.

✨ Key benefits:
🔄 Cumulative learning over time
📖 Transparent, inspectable strategies
🔌 Works with any OpenAI-compatible API
⚡ Simple integration: just add "spl-" prefix to your model

Built as an open-source plugin in optillm. After 500 queries, our system developed 129 strategies and refined 97 of them!

This feels like a genuine step toward AI that learns from experience while staying completely interpretable.

🔗 GitHub: https://github.com/codelion/optillm/tree/main/optillm/plugins/spl
📖 Full article: https://huggingface.co/blog/codelion/system-prompt-learning
🐦 Original Karpathy tweet: https://x.com/karpathy/status/1921368644069765486

Have you experimented with advanced system prompting? What strategies would you want your LLM to learn?
reacted to dhruv3006's post with 🚀 about 7 hours ago
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App-Use : Create virtual desktops for AI agents to focus on specific apps.

App-Use lets you scope agents to just the apps they need. Instead of full desktop access, say "only work with Safari and Notes" or "just control iPhone Mirroring" - visual isolation without new processes for perfectly focused automation.

Running computer-use on the entire desktop often causes agent hallucinations and loss of focus when they see irrelevant windows and UI elements. App-Use solves this by creating composited views where agents only see what matters, dramatically improving task completion accuracy

What you can build: Research agents working in Safari while writing agents draft in Notes, iPhone automation for messages and reminders, parallel testing across isolated app sessions, or teams of specialized agents working simultaneously without interference.

Currently macOS-only (Quartz compositing engine).

Read the full guide: https://trycua.com/blog/app-use

Github : https://github.com/trycua/cua
reacted to frascuchon's post with 👍 about 7 hours ago
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640
Hey! I built RAG MCP Server Space, a simple Gradio MCP server for RAG systems that allows you to search relevant results without passing huge contexts to your LLM.

You can use this space to integrate with your agents and improve the efficiency of your search results. Feel free to try it out and let me know if you have any feedback or questions!

frascuchon/rag-mcp-server

Thanks for checking it out!
reacted to MonsterMMORPG's post with 👀 about 9 hours ago
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1106
CausVid LoRA V2 of Wan 2.1 Brings Massive Quality Improvements, Better Colors and Saturation > https://youtu.be/1rAwZv0hEcU

Tutorial video : https://youtu.be/1rAwZv0hEcU

CausVid LoRA V2 of Wan 2.1 is just amazing. In this tutorial video I will show you how to use the most powerful video generation model Wan 2.1 with CausVid LoRA effortlessly. Normally, Wan 2.1 requires 50 steps to get excellent results. With CausiVid LoRA we get such excellent results only in 8 steps. Morever, with newest version 2, now the quality is almost identical to base Wan 2.1. I will show how to download and use in SwarmUI with 1-click to apply download and apply presets. We will also leverage of ComfyUI and fastest attention (Sage Attention).

🔗Follow below link to download the zip file that contains SwarmUI installer and AI models downloader Gradio App - the one used in the tutorial ⤵️
▶️ https://www.patreon.com/posts/SwarmUI-Installer-AI-Videos-Downloader-114517862

▶️ CausVid Main Tutorial : https://youtu.be/fTzlQ0tjxj0

▶️ How to install SwarmUI main tutorial : https://youtu.be/fTzlQ0tjxj0

🔗Follow below link to download the zip file that contains ComfyUI 1-click installer that has all the Flash Attention, Sage Attention, xFormers, Triton, DeepSpeed, RTX 5000 series support ⤵️
▶️ https://www.patreon.com/posts/Advanced-ComfyUI-1-Click-Installer-105023709

🔗 Python, Git, CUDA, C++, FFMPEG, MSVC installation tutorial - needed for ComfyUI ⤵️
▶️ https://youtu.be/DrhUHnYfwC0

🔗 SECourses Official Discord 10500+ Members ⤵️
▶️ https://discord.com/servers/software-engineering-courses-secourses-772774097734074388

🔗 Stable Diffusion, FLUX, Generative AI Tutorials and Resources GitHub ⤵️
▶️ https://github.com/FurkanGozukara/Stable-Diffusion

🔗 SECourses Official Reddit - Stay Subscribed To Learn All The News and More ⤵️
▶️ https://www.reddit.com/r/SECourses/

reacted to maximuspowers's post with 🤗 about 9 hours ago
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425
♔ Chess players:
I made an app that encodes chess moves and initiative as musical notes. I'd love to hear ideas from more advanced players about how I could improve this.

My vision for this project was to improve pattern recognition of openings, tactics, and positions through artificial synesthesia.

Please try it out and let me know if you have any ideas for it:
maximuspowers/musical-chess

Thanks😁
reacted to YerbaPage's post with 👍 about 9 hours ago
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1090
Curated list of **Next Gen Code Generation** papers & benchmarks! 🔥 with 80+ ⭐️ now!

Stay ahead with the latest in:
✅ Repo-level Issue Resolution (SWE-bench, Agents)
✅ Repo-level Code Completion (Repo understanding)
✅ Datasets & Benchmarks

👉 Check it out: https://github.com/YerbaPage/Awesome-Repo-Level-Code-Generation 🔥
💡PRs are welcomed!
reacted to merve's post with 🔥 about 9 hours ago
reacted to ginipick's post with 🔥 1 day ago
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2987
🎨 FLUX VIDEO Generation - All-in-One AI Image/Video/Audio Generator

🚀 Introduction
FLUX VIDEO Generation is an all-in-one AI creative tool that generates images, videos, and audio from text prompts, powered by NVIDIA H100 GPU for lightning-fast processing!

ginigen/Flux-VIDEO

✨ Key Features
1️⃣ Text → Image → Video 🖼️➡️🎬

Generate high-quality images from Korean/English prompts
Transform still images into natural motion videos
Multiple size presets (Instagram, YouTube, Facebook, etc.)
Demo: 1-4 seconds / Full version: up to 60 seconds

2️⃣ Image Aspect Ratio Change 🎭

Freely adjust image aspect ratios
Expand images with outpainting technology
5 alignment options (Center, Left, Right, Top, Bottom)
Real-time preview functionality

3️⃣ Video + Audio Generation 🎵

Add AI-generated audio to videos
Korean prompt support (auto-translation)
Context-aware sound generation
Powered by MMAudio technology

🛠️ Tech Stack

Image Generation: FLUX, Stable Diffusion XL
Video Generation: TeaCache optimization
Audio Generation: MMAudio (44kHz high-quality)
Outpainting: ControlNet Union
Infrastructure: NVIDIA H100 GPU for ultra-fast generation

💡 How to Use

Select your desired tab
Enter your prompt (Korean/English supported!)
Adjust settings
Click generate button

🎯 Use Cases

📱 Social media content creation
🎥 YouTube Shorts/Reels
📊 Presentation materials
🎨 Creative artwork
🎵 Background sound generation
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reacted to Kseniase's post with 🚀 1 day ago
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13 Awesome MCP Servers

MCP changed how agents connect with tools.

After writing the most read explanation of MCP on Hugging Face (https://huggingface.co/blog/Kseniase/mcp), we chose this 13 awesome MCP servers that you can work with:

1. Agentset MCP -> https://github.com/agentset-ai/mcp-server
For efficient and quick building of intelligent, doc-based apps using open-source Agentset platform for RAG

2. GitHub MCP Server -> https://github.com/github/github-mcp-server
Integrates GitHub APIs into your workflow, allowing to build AI tools and apps that interact with GitHub's ecosystem

3. arXiv MCP -> https://github.com/andybrandt/mcp-simple-arxiv
Allows working with research papers on arXiv through effective search and access to their metadata, abstracts, and links

4. MCP Run Python -> https://github.com/pydantic/pydantic-ai/tree/main/mcp-run-python
Enables to run Python code in a sandbox via Pyodide in Deno, so it can be isolated from the rest of the operating system

5. Safe Local Python Executor -> https://github.com/maxim-saplin/mcp_safe_local_python_executor
A lightweight tool for running LLM-generated Python code locally, using Hugging Face’s LocalPythonExecutor (from smolagents framework) and exposing it via MCP for AI assistant integration

6. Cursor MCP Installer -> https://github.com/matthewdcage/cursor-mcp-installer
Allows to automatically add MCP servers to Cursor for development convenience

7. Basic Memory -> https://memory.basicmachines.co/docs/introduction
This knowledge management system connects to LLMs and lets you build a persistent semantic graph from AI conversations with AI agents

Read further in the comments 👇

If you like it, also subscribe to the Turing Post: https://www.turingpost.com/subscribe
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reacted to azettl's post with 🤗 1 day ago
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I'm currently doing the MCP Course, and with the announcement of the Gradio Agents & MCP Hackathon, I couldn't sit still.

I decided to try creating a small MCP server that goes beyond the simple course text sentiment example. Additionally, I wanted to give vibe coding another try 😅, especially since this is a nice isolated use case. And with the release of Claude Sonnet 4, it seemed like a great idea.

So, here is my (𝘰𝘳 𝘪𝘴 𝘪𝘵 𝘊𝘭𝘢𝘶𝘥𝘦'𝘴?) MCP server to analyze your website statistics using the Plausible Stats API.

➡️ 𝗧𝗿𝘆 𝗶𝘁 𝗼𝘂𝘁 𝗵𝗲𝗿𝗲: azettl/mcp-plausible and snoop into my website statistics.
reacted to VirtualOasis's post with 🚀 1 day ago
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3315
Agent Mesh
Agent Mesh is an exciting framework where autonomous AI agents collaborate in a connected ecosystem, sharing information and dynamically tackling complex tasks. Think of it as a network of smart agents collaborating seamlessly to get things done!

Agents share tasks and data, boosting efficiency.
Scalability: Easily add new agents to handle bigger challenges.

reacted to onekq's post with 👍 1 day ago
reacted to ProCreations's post with 👍 1 day ago
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Introducing my custom AI lab!

This huggingface shows a bunch of fundamental visuals of AI’s training in real time.

ProCreations/ai-labs

Updates coming soon with a walk through mode that teaches you what it all means!

Meanwhile if you want to learn about AI and not just see it,
ProCreations/learn-ai
reacted to shukdevdatta123's post with 👍 2 days ago
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229
Introducing NeuroScope-Ai: An advanced agentic AI chatbot capable of intelligently searching for information based on your preferences. It can prioritize your preferred domains while avoiding specified domains you do not want it to access, ensuring it delivers accurate and tailored responses to user queries.

shukdevdatta123/NeuroScope-AI


reacted to ginipick's post with 🔥 2 days ago
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3340
🎨 AI Hairstyle Changer - Transform with 93 Styles! 💇‍♀️✨

🚀 Introduction
Experience 93 different hairstyles and 29 hair colors in real-time with your uploaded photo!
Transform your look instantly with this AI-powered Gradio web app.


✨ Key Features

📸 Simple 3 Steps
Upload Photo - Upload a front-facing photo
Select Style - Choose from 93 hairstyles
Pick Color - Click your desired color from 29 color palette options


💫 Diverse Hairstyles (93 types)

🎯 Short Cuts: Pixie Cut, Bob, Lob, Crew Cut, Undercut
🌊 Waves: Soft Waves, Hollywood Waves, Finger Waves
🎀 Braids: French Braid, Box Braids, Fishtail Braid, Cornrows
👑 Updos: Chignon, Messy Bun, Top Knot, French Twist
🌈 Special Styles: Space Buns, Dreadlocks, Mohawk, Beehive

🎨 Hair Color Palette (29 colors)

🤎 Natural Colors: Black, Browns, Blonde variations
❤️ Red Tones: Red, Auburn, Copper, Burgundy
💜 Fashion Colors: Blue, Purple, Pink, Green, Rose Gold
⚪ Cool Tones: Silver, Ash Blonde, Titanium

🌟 Key Advantages

⚡ Fast Processing: Get results in just 10-30 seconds
🎯 High Accuracy: Natural-looking transformations with AI technology
💎 Professional Quality: High-resolution output suitable for social media
🔄 Unlimited Trials: Try as many combinations as you want
📱 User-Friendly: Intuitive interface with visual color palette


💡 Perfect For

💈 Salon Consultations: Show clients potential new looks before cutting
🛍️ Personal Styling: Experiment before making a big change
🎭 Entertainment: Fun transformations for social media content
🎬 Creative Projects: Character design and visualization
👗 Fashion Industry: Match hairstyles with outfits and makeup
📸 Photography: Pre-visualization for photoshoots

LINK: ginipick/Change-Hair
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reacted to prithivMLmods's post with 👍❤️ 2 days ago
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OpenAI, Google, Hugging Face, and Anthropic have released guides and courses on building agents, prompting techniques, scaling AI use cases, and more. Below are 10+ minimalistic guides and courses that may help you in your progress. 📖

⤷ Agents Companion : https://www.kaggle.com/whitepaper-agent-companion
⤷ Building Effective Agents : https://www.anthropic.com/engineering/building-effective-agents
⤷ Guide to building agents by OpenAI : https://cdn.openai.com/business-guides-and-resources/a-practical-guide-to-building-agents.pdf
⤷ Prompt engineering by Google : https://www.kaggle.com/whitepaper-prompt-engineering
⤷ Google: 601 real-world gen AI use cases : https://cloud.google.com/transform/101-real-world-generative-ai-use-cases-from-industry-leaders
⤷ Prompt engineering by IBM : https://www.ibm.com/think/topics/prompt-engineering-guide
⤷ Prompt Engineering by Anthropic : https://docs.anthropic.com/en/docs/build-with-claude/prompt-engineering/overview
⤷ Scaling AI use cases : https://cdn.openai.com/business-guides-and-resources/identifying-and-scaling-ai-use-cases.pdf
⤷ Prompting Guide 101 : https://services.google.com/fh/files/misc/gemini-for-google-workspace-prompting-guide-101.pdf
⤷ AI in the Enterprise by OpenAI : https://cdn.openai.com/business-guides-and-resources/ai-in-the-enterprise.pdf

by HF🤗 :
⤷ AI Agents Course by Huggingface : https://huggingface.co/learn/agents-course/unit0/introduction
⤷ Smol-agents Docs : https://huggingface.co/docs/smolagents/en/tutorials/building_good_agents
⤷ MCP Course by Huggingface : https://huggingface.co/learn/mcp-course/unit0/introduction
⤷ Other Course (LLM, Computer Vision, Deep RL, Audio, Diffusion, Cookbooks, etc..) : https://huggingface.co/learn
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reacted to sequelbox's post with 👍 3 days ago
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NEW RELEASE: we've brought Esper 3 to the new deepseek-ai/DeepSeek-R1-0528-Qwen3-8B model!

- A full-stack software assistant: a reasoning finetune focused on coding, architecture, and DevOps using the Titanium and Tachibana datasets!
- Improved general and creative reasoning skills, powered by the Raiden dataset.

Get the newest Esper 3: ValiantLabs/DeepSeek-R1-0528-Qwen3-8B-Esper3
Support our releases: sequelbox/SupportOpenSource

more on the way next week!

celestially yours ;)
allegra
reacted to BFFree's post with 🔥 3 days ago
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I am a shy artist. Primarily because I don't get motivation from sharing art publicly. I see so much new art daily online that once I begin thinking about where I fit in the mental fatigue becomes counter productive for me.

Recently I shared an album of hundreds of creations with a friend (and singular art fan) and he asked some questions that I felt were interesting enough to create this post on my process and what it teaches me vs what I am seeking.

Specifically I have learned to take ink drawings and create renderings that reveal my actual intention. My digital art goal is to recreate natural details into characters and landscapes that are imagined and deal with my affection for abstraction, deconstruction and humor.

My drawing goals are to be humorous and crafty about how things can be rendered just slightly incorrect to make the viewer see something familiar and recognizable even when its nonsense.

My process is using hysts/ControlNet-v1-1 with Lineart, 50 steps, 14 guidance scale and I give minimal descriptions that are often plain. Example "Really real old dog, plant, and another old dog, with an alligator turtle, posing for a photography portrait".

In the past few months I started taking the ControlNet render to multimodalart/flux-style-shaping and mashing up styles. Here I used a portrait of a Tortise and a dog laying next to each other on a reflective tile floor.

Last night, I took the Flux output and had it described using WillemVH/Image_To_Text_Description which was very accurate given the image.

I then fed the prompt back into Alpha-VLLM/Lumina-Image-2.0

The last step confirmed why I prefer using sketches to language. One, I am a visual artist therefore I have much better nuance with the drawings than with words. Two, my minds eye looks for the distorted. Three MOR FUN.



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reacted to merve's post with 🔥 3 days ago
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HOT: MiMo-VL new 7B vision LMs by Xiaomi surpassing gpt-4o (Mar), competitive in GUI agentic + reasoning tasks ❤️‍🔥 XiaomiMiMo/mimo-vl-68382ccacc7c2875500cd212

not only that, but also MIT license & usable with transformers 🔥