Mrdesigner14 (Kg Ghost)

🍅 Glif App's Remixes feature allows you to slap a logo onto anything, seamlessly integrating the input image (logo) into various contexts. The result is stunning remixes that blend the input logo with generated images (img2img logo mapping) for incredible outcomes.

Check out Any Logo Anywhere remixes on Glif: [Glif Remixes](https://glif.app/glifs/cm3o7dfsd002610z48sz89yih/remixes)

🌐The browser extension enables thousands of Glif-based img2img workflows on any image you find online. Experience Glif Remix with WebAI: [Chrome Extension](https://chromewebstore.google.com/detail/glif-remix-the-web-with-a/abfbooehhdjcgmbmcpkcebcmpfnlingo)

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🤗Have fun with the cool stuff !!
@prithivMLmods

reacted to singhsidhukuldeep's post with 🔥 28 days ago

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2299

Good folks at @nvidia and @Tsinghua_Uni have released LLAMA-MESH - A Revolutionary Approach to 3D Content Generation!

This innovative framework enables the direct generation of 3D meshes from natural language prompts while maintaining strong language capabilities.

Here is the Architecture & Implementation!

>> Core Components

Model Foundation
- If you haven't guessed it yet, it's built on the LLaMA-3.1-8B-Instruct base model
- Maintains original language capabilities while adding 3D generation
- Context length is set to 8,000 tokens

3D Representation Strategy
- Uses the OBJ file format for mesh representation
- Quantizes vertex coordinates into 64 discrete bins per axis
- Sorts vertices by z-y-x coordinates, from lowest to highest
- Sorts faces by the lowest vertex indices for consistency

Data Processing Pipeline
- Filters meshes to a maximum of 500 faces for computational efficiency
- Applies random rotations (0°, 90°, 180°, 270°) for data augmentation
- Generates ~125k mesh variations from 31k base meshes
- Uses Cap3D-generated captions for text descriptions

>> Training Framework

Dataset Composition
- 40% Mesh Generation tasks
- 20% Mesh Understanding tasks
- 40% General Conversation (UltraChat dataset)
- 8x training turns for generation, 4x for understanding

Training Configuration
- Deployed on 32 A100 GPUs (for Nvidia, this is literally in-house)
- 21,000 training iterations
- Global batch size: 128
- AdamW optimizer with a 1e-5 learning rate
- 30-step warmup with cosine scheduling
- Total training time: approximately 3 days (based on the paper)

This research opens exciting possibilities for intuitive 3D content creation through natural language interaction. The future of digital design is conversational!

liked a Space 29 days ago

Runtime error

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Text Behind Image

Text Behind Image using birefnet-lite for background removal

reacted to prithivMLmods's post with 😎❤️🔥 about 1 month ago

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New adapt.s for dev 🍔

Hosted -> prithivMLmods/FLUX-LoRA-DLC

✨Teen Outfit: prithivMLmods/Teen-Outfit
✨Dark Pink: prithivMLmods/Dark-Thing-Flux-LoRA
✨Shadow Projection: prithivMLmods/Shadow-Projection-Flux-LoRA
✨Abstract Cartoon: prithivMLmods/Abstract-Cartoon-Flux-LoRA
✨Street Bokeh: prithivMLmods/Street-Bokeh-Flux-LoRA
✨Fine Detailed: prithivMLmods/Flux-Realism-FineDetailed
✨Bold Shadows: prithivMLmods/Bold-Shadows-Flux-LoRA
✨Yellow Laser: prithivMLmods/Yellow-Laser-Flux-LoRA

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🎉LoRA Collection: prithivMLmods/flux-lora-collections-66dd5908be2206cfaa8519be

🎉LoRA Spaces: prithivMLmods/lora-space-collections-6714b72e0d49e1c97fbd6a32

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.@prithivMLmods 🤗

reacted to MonsterMMORPG's post with 🔥 about 1 month ago

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4044

How To Use Mochi 1 Open Source Video Generation Model On Your Windows PC, RunPod and Massed Compute

Tutorial Link : https://youtu.be/iqBV7bCbDJY

Mochi 1 from Genmo is the newest state-of-the-art Open Source video generation model that you can use for free on your computer. This model is a breakthrough like the very first Stable Diffusion model but this time it is starting for the video generation models. In this tutorial, I am going to show you how to use Genmo Mochi 1 video generation model on your computer, on windows, locally with the most advanced and very easy to use SwarmUI. SwarmUI as fast as ComfyUI but also as easy as using Automatic1111 Stable Diffusion web UI. Moreover, if you don’t have a powerful GPU to run this model locally, I am going to show you how to use this model on the best cloud providers RunPod and Massed Compute.

🔗 Public Open Access Article Used in Video ⤵️
▶️ https://www.patreon.com/posts/106135985

Amazing Ultra Important Tutorials with Chapters and Manually Written Subtitles / Captions
Stable Diffusion 3.5 Large How To Use Tutorial With Best Configuration and Comparison With FLUX DEV : https://youtu.be/-zOKhoO9a5s

FLUX Full Fine-Tuning / DreamBooth Tutorial That Shows A Lot Info Regarding SwarmUI Latest : https://youtu.be/FvpWy1x5etM

Full FLUX Tutorial — FLUX Beats Midjourney for Real : https://youtu.be/bupRePUOA18

Main Windows SwarmUI Tutorial (Watch To Learn How to Use)

How to install and use. You have to watch this to learn how to use SwarmUI
Has 70 chapters and manually fixed captions : https://youtu.be/HKX8_F1Er_w