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README.md
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##
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TinyPokemonDiffusion is a lightweight DDPM-based generative model trained on Pokémon images.
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---
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##
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| Component | Value |
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|------------------|------|
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---
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##
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- Full DDPM implementation from scratch
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- Custom UNet with attention blocks
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---
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##
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The model generates:
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## THE INITIAL IDEA WAS A STUDENT U-NET FROM A TEACHER U-NET, BUT THIS WAS DISCONTINUED BECAUSE THE TEACHER WAS INITIALIZATED WITH RANDOM WEIGHTS, THAT WOULD KILL THE STUDENT LEARNING
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##
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### Generate images
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--seed 42
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```
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Generated images are saved as a horizontal grid:
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outputs/generated.png
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>>
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Unconditional model (no prompts)
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Early training stage
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No DDIM (yet)
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>>
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This project demonstrates that:
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Text-to-image (v2.0)
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DDIM sampling
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Larger model variants
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Most diffusion research focuses on scaling up.
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What is the minimum viable diffusion model?
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MIT
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Hugging Face datasets
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PyTorch
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The open-source AI community
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Give it a star and follow the evolution to v2.0(conditional)
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## Overview
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TinyPokemonDiffusion is a lightweight DDPM-based generative model trained on Pokémon images.
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---
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## Specifications
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| Component | Value |
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|------------------|------|
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---
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## Features
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- Full DDPM implementation from scratch
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- Custom UNet with attention blocks
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---
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## Results
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The model generates:
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---
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## Usage
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### Generate images
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--seed 42
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```
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Output
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Generated images are saved as a horizontal grid:
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outputs/generated.png
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>> Limitations
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Unconditional model (no prompts)
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Early training stage
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No DDIM (yet)
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>> Research Direction
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This project demonstrates that:
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Text-to-image (v2.0)
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DDIM sampling
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Larger model variants
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Motivation
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Most diffusion research focuses on scaling up.
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What is the minimum viable diffusion model?
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License
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MIT
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Acknowledgments
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Hugging Face datasets
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PyTorch
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The open-source AI community
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If you like this project:
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Give it a star and follow the evolution to v2.0(conditional)
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## Other
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THE INITIAL IDEA WAS A STUDENT U-NET FROM A TEACHER U-NET, BUT THIS WAS DISCONTINUED BECAUSE THE TEACHER WAS INITIALIZATED WITH RANDOM WEIGHTS, THAT WOULD KILL THE STUDENT LEARNING
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