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nyuuzyou

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posted an update 2 days ago
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1152
๐ŸŽฎ GoodGame.ru Clips Dataset - nyuuzyou/goodgame

A collection of 39,280 video clips metadata from GoodGame.ru streaming platform featuring:

- Complete clip information including direct video URLs and thumbnails
- Streamer details like usernames and avatars
- Engagement metrics such as view counts
- Game categories and content classifications
- Released under Creative Commons Zero (CC0) license

This extensive clips collection provides a valuable resource for developing and evaluating video-based AI applications, especially in Russian gaming and streaming contexts.
reacted to nroggendorff's post with ๐Ÿ˜” 2 days ago
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3025
im so tired
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reacted to etemiz's post with ๐Ÿ‘€ 6 days ago
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2268
As more synthetic datasets are made, we move slowly away from human alignment.
  • 4 replies
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replied to their post 7 days ago
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Yes, I don't want to pollute my subscribers' feeds (I've already had several people unsubscribe from me due to spam with reports).

Thanks for your work. Let me know if there is anything I can do to reduce your workload with my reports.

posted an update 7 days ago
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809
๐ŸŽ“ Soloby.ru Russian Q&A Dataset - nyuuzyou/soloby

A collection of 744,131 educational question-answer pairs featuring:

- Complete Q&A content from the Soloby.ru educational platform
- Rich metadata including timestamps, authors, and categories
- Detailed question titles and corresponding answers
- Native Russian language content across various subjects
- Released under Creative Commons Zero (CC0) license

This extensive Q&A collection provides a valuable resource for developing and evaluating Russian language AI applications, especially in educational contexts. The structured format and diverse subject coverage make it ideal for training models to understand and generate Russian educational content.
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reacted to jwlben11's post with ๐Ÿค— 9 days ago
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2129
What is the use of hugginface? How can I get up to speed on ML and AI and how to use this platform? Would be nice if there was a get started here section.
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reacted to cutechicken's post with ๐Ÿ”ฅ๐Ÿ‘€ 10 days ago
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3460
๐ŸŽฎ Introduction to the World's First 3D Tank Game Created Solely with Generative AI ๐Ÿš€
The advancement of AI technology is revolutionizing game development paradigms. I embarked on a challenge to create a 3D tank game using "only AI assistance," pushing the boundaries of what's possible in AI-driven game development. ๐Ÿค–
Following the success of my first 2D tank game ( cutechicken/tankwar) ๐ŸŽฏ, I ventured into the more challenging realm of 3D FPS game development. Remarkably, using Hugging Face's AI tool ( VIDraft/mouse1), the basic game framework was generated in just one minute โšก. The 3D modeling ( ginipick/SORA-3D) and sound effects ( fantaxy/Sound-AI-SFX) were also easily created with AI assistance.
The resulting game ( cutechicken/TankWar3D) represents arguably the world's first 3D FPS game created primarily with generative AI. 90% was accomplished through AI capabilities, with the remaining 10% comprising my post-processing work. ๐ŸŽ‰
Key Technical Features: ๐Ÿ› ๏ธ

Complete 3D rendering system using Three.js ๐Ÿ–ฅ๏ธ
Real-time physics-based collision detection and handling ๐Ÿ’ฅ
Dynamic shadow and lighting system โ˜€๏ธ
Real-time radar and enemy tracking system ๐ŸŽฏ
Advanced particle effects system (explosions, smoke, fire) ๐Ÿ’ซ
Dynamic sound system (engine, firing, explosion sounds) ๐Ÿ”Š
AI-driven enemy strategy system (pursuit, evasion, combat) ๐Ÿค–
Terrain-based tank tilt adjustment ๐ŸŒ
Real-time crosshair targeting system ๐ŸŽฏ
Dynamic UI system (health bars, ammo, score) ๐Ÿ“Š

Technical Implementation: โš™๏ธ

Physics Engine: ๐ŸŽณ
Custom collision detection system
Dynamic obstacle handling
Real-time terrain interaction


AI Systems: ๐Ÿง 
State-based AI behavior patterns
Dynamic pathfinding
Tactical decision-making system

Graphics: ๐ŸŽจ
PBR-based rendering
Dynamic particle system
Real-time shadow mapping
reacted to prithivMLmods's post with ๐Ÿ”ฅ 10 days ago
reacted to csabakecskemeti's post with ๐Ÿ‘ 10 days ago
reacted to DualityAI-RebekahBogdanoff's post with ๐Ÿ”ฅ 14 days ago
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2790
Training YOLO with Synthetic Data from Duality AI's Falcon๐ŸŽฎ๐Ÿ“Š
Hi Huggingface community! ๐Ÿ‘‹
Duality.ai is excited to share a Google Colab notebook that demonstrates how easy it is to train YOLOv8 using synthetic data generated in our Falcon simulation softwareโ€”and see it work in the real world!

https://storage.googleapis.com/duality-public-share/syntheticDataWorks.ipynb

Train using synthetic images of a cereal box digital twin, then see it work on real-world images.๐Ÿฅฃ๐Ÿ’›

Instructions for running this can be found here: https://falcon.duality.ai/secure/documentation/see-synth-work-no-specs
You'll have to create an account to view it, but the notebook by itself explains itself very well.

This method is a game-changer for cost-effective, scalable, and customizable datasets in computer vision.
Why Synthetic Data?๐Ÿค”
- Precise Annotations: Get bounding boxes, segmentation masks, and more without manual effort.
- Customizable Scenarios: Simulate diverse conditions like lighting and weather.
Whatโ€™s in the Notebook?๐Ÿ““
- Training & Evaluation: Train YOLOv8 with synthetic data and test its performance on real-world samples.
Try it Out! ๐Ÿš€
Access the notebook here:
https://storage.googleapis.com/duality-public-share/syntheticDataWorks.ipynb
Itโ€™s fully documented and ready for you to explore and adapt.

Want to create your own custom datasets? Checkout Falcon here:
https://falcon.duality.ai/auth/sign-up
https://www.duality.ai/edu

Letโ€™s Discuss!๐Ÿ’ฌ
How are you using synthetic data in ML projects? Letโ€™s connectโ€”drop your thoughts or questions below or on our Discord! https://discord.com/invite/dualityfalconcommunity
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reacted to julien-c's post with โค๏ธ 15 days ago
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7612
After some heated discussion ๐Ÿ”ฅ, we clarify our intent re. storage limits on the Hub

TL;DR:
- public storage is free, and (unless blatant abuse) unlimited. We do ask that you consider upgrading to PRO and/or Enterprise Hub if possible
- private storage is paid above a significant free tier (1TB if you have a paid account, 100GB otherwise)

docs: https://huggingface.co/docs/hub/storage-limits

We optimize our infrastructure continuously to scale our storage for the coming years of growth in Machine learning, to the benefit of the community ๐Ÿ”ฅ

cc: @reach-vb @pierric @victor and the HF team
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replied to julien-c's post 15 days ago
posted an update 17 days ago
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1503
โœˆ๏ธ Aircraft Dataset & Generation Model nyuuzyou/aircraft-images & nyuuzyou/AircraftFLUX-LoRA

Dataset Features:
โ€ข 165,340 high-res aircraft images with metadata
โ€ข Machine-generated English captions
โ€ข Detailed aircraft specs, registration & flight info
โ€ข Environmental context descriptions

LoRA model specializes in:
โ€ข Realistic aircraft generation
โ€ข Accurate technical details for unpopular airplanes compared to black-forest-labs/FLUX.1-schnell
โ€ข Proper airline liveries
โ€ข Contextual aviation scenes
reacted to reach-vb's post with ๐Ÿ”ฅ 19 days ago
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3206
VLMs are going through quite an open revolution AND on-device friendly sizes:

1. Google DeepMind w/ PaliGemma2 - 3B, 10B & 28B: google/paligemma-2-release-67500e1e1dbfdd4dee27ba48

2. OpenGVLabs w/ InternVL 2.5 - 1B, 2B, 4B, 8B, 26B, 38B & 78B: https://huggingface.co/collections/OpenGVLab/internvl-25-673e1019b66e2218f68d7c1c

3. Qwen w/ Qwen 2 VL - 2B, 7B & 72B: Qwen/qwen2-vl-66cee7455501d7126940800d

4. Microsoft w/ FlorenceVL - 3B & 8B: https://huggingface.co/jiuhai

5. Moondream2 w/ 0.5B: https://huggingface.co/vikhyatk/

What a time to be alive! ๐Ÿ”ฅ
replied to Duskfallcrew's post 20 days ago
replied to Duskfallcrew's post 21 days ago
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I'm waiting for at least an announcement explaining what's going on and at most how this quota is calculated

replied to nroggendorff's post 21 days ago
posted an update 21 days ago
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833
what a shame
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