Instructions to use redrob-labs/redrob-image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use redrob-labs/redrob-image with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("redrob-labs/redrob-image", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 1,694 Bytes
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Copyright 2026 Redrob (https://redrob.io)
Copyright 2026 Janghoon Lee (https://www.janghoonlee.com)
Date: August 5, 2026
Licensed under the Apache License, Version 2.0.
https://www.apache.org/licenses/LICENSE-2.0
This distribution is a modified derivative of Z-Image-Turbo.
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Upstream attribution
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This product includes model weights derived from:
Tongyi-MAI / Z-Image-Turbo
https://huggingface.co/Tongyi-MAI/Z-Image-Turbo
https://github.com/Tongyi-MAI/Z-Image
Licensed under the Apache License, Version 2.0.
Copyright notices from the upstream project are retained to the extent
applicable.
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Modifications by Redrob (built by Janghoon Lee)
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- Style adapter baked into the UNET at strength 0.7 (ComfyUI
LoraLoaderModelOnly -> state_dict bake).
- Branded the distribution artifact as Redrob Image
(modelspec + redrob.* safetensors metadata).
- Packaged for ComfyUI UNETLoader (diffusion_models layout) and as a
Diffusers ZImageTransformer2DModel under transformer/.
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Companion weights (not in this package by default)
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Runtime still typically requires (from Comfy-Org / Tongyi packs):
- qwen_3_4b_fp8_mixed.safetensors (text encoder)
- ae.safetensors (VAE)
See README.md.
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