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Sd Class Butterflies 32 Using Mse Loss
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Sd Class Butterflies 32 Using Mse Loss

Developed by AlokBharadwaj
This is an unconditional image generation model based on the diffusion model, specifically designed to generate cute butterfly images.
Image GenerationOpen Source License:MIT#Unconditional image generation#Butterfly image generation#Diffusion model
Downloads 5
Release Time : 12/7/2024

Model Overview

This model is a diffusion model for unconditional generation of cute butterfly images. It is built based on PyTorch and the Diffusers library and trained using the MSE loss function.

Model Features

Unconditional image generation
Capable of generating high-quality butterfly images without input conditions
Based on MSE loss
Trained using the Mean Squared Error (MSE) as the loss function
Small model
A small model with an inference resolution of 32x32, suitable for fast generation

Model Capabilities

Unconditional image generation
Butterfly image generation

Use Cases

Creative design
Butterfly pattern generation
Provide creative inspiration for designers on butterfly patterns
Generate diverse butterfly images
Educational demonstration
Diffusion model teaching
Used to demonstrate the basic working principle of the diffusion model
Intuitively show the unconditional image generation process
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