Spaces:
Running on Zero
Running on Zero
metadata
title: PixelModel v6
emoji: 🖼️
colorFrom: yellow
colorTo: indigo
sdk: gradio
sdk_version: 6.22.0
app_file: app.py
short_description: 155M-parameter MMDiT text-to-image model
python_version: '3.12'
startup_duration_timeout: 30m
PixelModel v6
A 155M-parameter text-to-image diffusion transformer (MMDiT) that generates 256×256 images using rectified flow sampling. Features joint attention over T5 text tokens and CLIP pooled conditioning.
Model details
- Architecture: MMDiT with joint attention, 2D RoPE, QK-norm, SwiGLU
- Parameters: 155M trainable (411M total incl. frozen VAE + text encoders)
- Text encoders: T5-base (joint stream) + CLIP ViT-B/32 (global adaLN)
- VAE:
madebyollin/sdxl-vae-fp16-fix - Resolution: 256×256
- Sampling: 50 steps, CFG 3.0
Based on bench-labs/PixelModel-v6.