Runpod Blog.

Stable Diffusion breaks images into 512×512 “cells” at higher resolutions, often leading to distorted results when generating discrete objects like people. This post explains why and how to avoid it using the Hi-Res Fix.

Image Mixer lets you blend multiple source images into a hybrid input for img2img in Stable Diffusion. This guide walks through setup, usage, and how to generate new variations from your composite image.

Common errors when spinning up pods often stem from insufficient container space or RAM/VRAM. This post explains how to identify and fix both issues by selecting the right pod resources for your workload.

This tutorial walks you through deploying Oobabooga’s Text Generation WebUI using the RunPod template. Includes steps for loading Pygmalion 6B and customizing your chatbot.

Learn how to remix existing images using ControlNet and Stable Diffusion on Runpod—perfect for creative experimentation and AI-powered visual iteration.

Learn how to use Runpod’s DreamBooth API to automate training and image generation. This guide covers preparing training data, sending requests via Postman, checking job status, and retrieving outputs, with tips for customizing models and prompts.

This guide explains how to launch a Runpod instance using the "Runpod Fast Stable Diffusion" template and train Dreambooth models using the included Jupyter notebooks. The post walks users through deploying the pod, connecting to JupyterLab, preparing instance images, setting training parameters, and running the Dreambooth training workflow. It also covers optional steps such as captioning, adding concept images, testing the trained model using Automatic1111, and uploading to Hugging Face.