README.md

metadata

title: Stable Diffusion Lab
emoji: 🎨
colorFrom: indigo
colorTo: pink
sdk: gradio
sdk_version: 6.30.0
python_version: '3.12'
app_file: app.py
pinned: false
license: creativeml-openrail-m
short_description: Explore Stable Diffusion with live denoising previews

Stable Diffusion Lab

A teaching Space for exploring text-to-image diffusion. Students can set:

• positive and negative prompt
• CFG scale (0.0 to 15.0) and denoising steps (4 to 48)
• sampler: Euler, Euler Ancestral, DDIM, UniPC
• checkpoint: Stable Diffusion 1.5 or Realistic Vision V6.0
• seed (or a random seed) and resolution (512x512 by default, 256 to 768 px)

While an image is generated, a live preview of the denoising is streamed to the page.

Hardware

Designed for a dedicated GPU (fp16, about 6 GB VRAM for both checkpoints). It also runs on CPU, but slowly. Both checkpoints load at startup, so the first build takes a few minutes while the weights download.

How the live preview works

The app runs its own denoising loop. At every step the U-Net predicts the noise, and from that prediction the app computes the model's current guess of the final image. That guess is decoded with TAESD, a tiny and fast VAE decoder. The final step uses the full VAE of the checkpoint.

Settings (Space variables)

Variable	Default	Meaning
SAFETY_CHECKER	1	Set to 0 to turn off the NSFW filter (it can flag harmless art)
MAX_CONCURRENT	1	Generations running at the same time
PRELOAD	1	Load both checkpoints at startup instead of on first use
SD15_REPO	sd-legacy/stable-diffusion-v1-5	Base model repo (the original runwayml repo is deprecated)
RV_REPO, RV_FILE	Realistic Vision V6.0 B1 noVAE, fp16 file	Finetuned checkpoint
RV_VAE_REPO	stabilityai/sd-vae-ft-mse	VAE for Realistic Vision, whose repo ships without one

Licenses

Both checkpoints use the CreativeML OpenRAIL-M license.