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Eric Chung PRO

DawnC

AI & ML interests

Computer Vision, LLM, Hybrid Architectures, MultiModel

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posted an update about 6 hours ago

PawMatchAI 🐾: The Complete Dog Breed Platform PawMatchAI offers a comprehensive suite of features designed for dog enthusiasts and prospective owners alike. This all-in-one platform delivers five essential tools to enhance your canine experience: 1. 🔍Breed Detection: Upload any dog photo and the AI accurately identifies breeds from an extensive database of 124+ different dog breeds. The system detects dogs in the image and provides confident breed identification results. 2.📊Breed Information: Access detailed profiles for each breed covering exercise requirements, typical lifespan, grooming needs, health considerations, and noise behavior - giving you complete understanding of any breed's characteristics. 3.📋 Breed Comparison : Compare any two breeds side-by-side with intuitive visualizations highlighting differences in care requirements, personality traits, health factors, and more - perfect for making informed decisions. 4.💡 Breed Recommendation: Receive personalized breed suggestions based on your lifestyle preferences. The sophisticated matching system evaluates compatibility across multiple factors including living space, exercise capacity, experience level, and family situation. 5.🎨 Style Transfer: Transform your dog photos into artistic masterpieces with five distinct styles: Japanese Anime, Classic Cartoon, Oil Painting, Watercolor, and Cyberpunk - adding a creative dimension to your pet photography. 👋Explore PawMatchAI today: https://huggingface.co/spaces/DawnC/PawMatchAI If you enjoy this project or find it valuable for your canine companions, I'd greatly appreciate your support with a Like❤️ for this project. #ArtificialIntelligence #MachineLearning #ComputerVision #PetTech #TechForLife

reacted to wolfram's post with 🔥 about 20 hours ago

Finally finished my extensive **Qwen 3 evaluations** across a range of formats and quantisations, focusing on **MMLU-Pro** (Computer Science). A few take-aways stood out - especially for those interested in local deployment and performance trade-offs: 1️⃣ **Qwen3-235B-A22B** (via Fireworks API) tops the table at **83.66%** with ~55 tok/s. 2️⃣ But the **30B-A3B Unsloth** quant delivered **82.20%** while running locally at ~45 tok/s and with zero API spend. 3️⃣ The same Unsloth build is ~5x faster than Qwen's **Qwen3-32B**, which scores **82.20%** as well yet crawls at <10 tok/s. 4️⃣ On Apple silicon, the **30B MLX** port hits **79.51%** while sustaining ~64 tok/s - arguably today's best speed/quality trade-off for Mac setups. 5️⃣ The **0.6B** micro-model races above 180 tok/s but tops out at **37.56%** - that's why it's not even on the graph (50 % performance cut-off). All local runs were done with LM Studio on an M4 MacBook Pro, using Qwen's official recommended settings. **Conclusion:** Quantised 30B models now get you ~98 % of frontier-class accuracy - at a fraction of the latency, cost, and energy. For most local RAG or agent workloads, they're not just good enough - they're the new default. Well done, Qwen - you really whipped the llama's ass! And to OpenAI: for your upcoming open model, please make it MoE, with toggleable reasoning, and release it in many sizes. *This* is the future!

updated a Space 1 day ago

DawnC/VisionScout

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PawMatchAI 🐾: The Complete Dog Breed Platform

PawMatchAI offers a comprehensive suite of features designed for dog enthusiasts and prospective owners alike. This all-in-one platform delivers five essential tools to enhance your canine experience:

1. 🔍Breed Detection: Upload any dog photo and the AI accurately identifies breeds from an extensive database of 124+ different dog breeds. The system detects dogs in the image and provides confident breed identification results.

2.📊Breed Information: Access detailed profiles for each breed covering exercise requirements, typical lifespan, grooming needs, health considerations, and noise behavior - giving you complete understanding of any breed's characteristics.

3.📋 Breed Comparison : Compare any two breeds side-by-side with intuitive visualizations highlighting differences in care requirements, personality traits, health factors, and more - perfect for making informed decisions.

4.💡 Breed Recommendation: Receive personalized breed suggestions based on your lifestyle preferences. The sophisticated matching system evaluates compatibility across multiple factors including living space, exercise capacity, experience level, and family situation.

5.🎨 Style Transfer: Transform your dog photos into artistic masterpieces with five distinct styles: Japanese Anime, Classic Cartoon, Oil Painting, Watercolor, and Cyberpunk - adding a creative dimension to your pet photography.

👋Explore PawMatchAI today:
DawnC/PawMatchAI

If you enjoy this project or find it valuable for your canine companions, I'd greatly appreciate your support with a Like❤️ for this project.

#ArtificialIntelligence #MachineLearning #ComputerVision #PetTech #TechForLife

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4457

VisionScout — Now with Video Analysis! 🚀

I’m excited to announce a major update to VisionScout, my interactive vision tool that now supports VIDEO PROCESSING, in addition to powerful object detection and scene understanding!

⭐️ NEW: Video Analysis Is Here!
🎬 Upload any video file to detect and track objects using YOLOv8.
⏱️ Customize processing intervals to balance speed and thoroughness.
📊 Get comprehensive statistics and summaries showing object appearances across the entire video.

What else can VisionScout do?

🖼️ Analyze any image and detect 80 object types with YOLOv8.
🔄 Switch between Nano, Medium, and XLarge models for speed or accuracy.
🎯 Filter by object classes (people, vehicles, animals, etc.) to focus on what matters.
📊 View detailed stats on detections, confidence levels, and distributions.
🧠 Understand scenes — interpreting environments and potential activities.
⚠️ Automatically identify possible safety concerns based on detected objects.

What’s coming next?
🔎 Expanding YOLO’s object categories.
⚡ Faster real-time performance.
📱 Improved mobile responsiveness.

My goal:
To bridge the gap between raw detection and meaningful interpretation.
I’m constantly exploring ways to help machines not just "see" but truly understand context — and to make these advanced tools accessible to everyone, regardless of technical background.

Try it now! 🖼️👉 DawnC/VisionScout

If you enjoy VisionScout, a ❤️ Like for this project or feedback would mean a lot and keeps me motivated to keep building and improving!

#ComputerVision #ObjectDetection #VideoAnalysis #YOLO #SceneUnderstanding #MachineLearning #TechForLife

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