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Document Diffusers format and add usage snippet

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  ---
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- license: cc-by-nc-4.0
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  language:
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  - en
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  pipeline_tag: text-to-image
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  <p><i>A cinematic fine-tune of Z-Image Base — tuned for presentation-ready output.</i></p>
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  <p>
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- <a href="https://www.rundiffusion.com/juggernaut-z?utm_source=huggingface&utm_medium=model_card&utm_campaign=juggernaut_z_v1&utm_content=cta_primary"><img alt="Try Juggernaut Z" src="https://img.shields.io/badge/%E2%96%B6%20Try%20Juggernaut%20Z-7C3AED?style=for-the-badge&labelColor=7C3AED"></a>&nbsp;<a href="https://www.rundiffusion.com/juggernaut-z-prompt-guide?utm_source=huggingface&utm_medium=model_card&utm_campaign=juggernaut_z_v1&utm_content=prompt_guide_badge"><img alt="Prompt Guide" src="https://img.shields.io/badge/Prompt%20Guide-1f1f23?style=for-the-badge"></a>&nbsp;<a href="https://huggingface.co/Tongyi-MAI/Z-Image"><img alt="Base Model: Z-Image" src="https://img.shields.io/badge/%F0%9F%A4%97%20Base%20Model-Z--Image-FFD21E?style=for-the-badge&labelColor=1f1f23"></a>&nbsp;<img alt="License: CC BY-NC 4.0" src="https://img.shields.io/badge/License-CC%20BY--NC%204.0-2ea44f?style=for-the-badge">
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  </p>
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  </div>
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  | `Juggernaut_Z_V1_by_RunDiffusion_q5_k_s-005.gguf` | GGUF · q5_k_s | |
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  | `Juggernaut_Z_V1_by_RunDiffusion_q4_k_m-002.gguf` | GGUF · q4_k_m | |
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  | `Juggernaut_Z_V1_by_RunDiffusion_q4_k_s-001.gguf` | GGUF · q4_k_s | Smallest footprint |
 
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- Use the `.safetensors` variants with the workflow that matches your local inference stack. Use the `.gguf` variants with a GGUF-compatible runtime.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## Links
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  Juggernaut Z is built on Z-Image Base — credit for the upstream base model belongs to the Z-Image team. This fine-tuned release is by **Team Juggernaut**, with training by **KandooAI**, published by **RunDiffusion**.
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- ## License & Commercial Use
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-
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- Juggernaut Z is released under **[CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/)**:
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-
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- - **BY** — attribute RunDiffusion / Team Juggernaut / KandooAI when sharing output.
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- - **NC** — **non-commercial use only**. You may not use the model — or its outputs in a workflow — for commercial purposes without a license.
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-
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- You are free to fine-tune, merge, build LoRAs, and otherwise modify the model for non-commercial purposes.
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- **For commercial licensing**, custom models, business inquiries, or consultation, contact **[juggernaut@rundiffusion.com](mailto:juggernaut@rundiffusion.com)**.
 
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  ---
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+ license: apache-2.0
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  language:
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  - en
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  pipeline_tag: text-to-image
 
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  <p><i>A cinematic fine-tune of Z-Image Base — tuned for presentation-ready output.</i></p>
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  <p>
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+ <a href="https://www.rundiffusion.com/juggernaut-z?utm_source=huggingface&utm_medium=model_card&utm_campaign=juggernaut_z_v1&utm_content=cta_primary"><img alt="Try Juggernaut Z" src="https://img.shields.io/badge/%E2%96%B6%20Try%20Juggernaut%20Z-7C3AED?style=for-the-badge&labelColor=7C3AED"></a>&nbsp;<a href="https://www.rundiffusion.com/juggernaut-z-prompt-guide?utm_source=huggingface&utm_medium=model_card&utm_campaign=juggernaut_z_v1&utm_content=prompt_guide_badge"><img alt="Prompt Guide" src="https://img.shields.io/badge/Prompt%20Guide-1f1f23?style=for-the-badge"></a>&nbsp;<a href="https://huggingface.co/Tongyi-MAI/Z-Image"><img alt="Base Model: Z-Image" src="https://img.shields.io/badge/%F0%9F%A4%97%20Base%20Model-Z--Image-FFD21E?style=for-the-badge&labelColor=1f1f23"></a>&nbsp;<img alt="License: Apache 2.0" src="https://img.shields.io/badge/License-Apache%202.0-2ea44f?style=for-the-badge">
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  </p>
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  </div>
 
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  | `Juggernaut_Z_V1_by_RunDiffusion_q5_k_s-005.gguf` | GGUF · q5_k_s | |
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  | `Juggernaut_Z_V1_by_RunDiffusion_q4_k_m-002.gguf` | GGUF · q4_k_m | |
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  | `Juggernaut_Z_V1_by_RunDiffusion_q4_k_s-001.gguf` | GGUF · q4_k_s | Smallest footprint |
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+ | `diffusers/` (subfolder) | 🤗 Diffusers format | Load with `DiffusionPipeline.from_pretrained(..., subfolder="diffusers")` |
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+ Use the `.safetensors` variants with the workflow that matches your local inference stack. Use the `.gguf` variants with a GGUF-compatible runtime. Use the `diffusers/` subfolder with the 🤗 Diffusers library — see below.
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+
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+ ## Use with 🤗 Diffusers
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+
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+ The `diffusers/` subfolder contains the model in standard 🤗 Diffusers format (`ZImagePipeline`) and can be loaded directly:
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+
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+ ```python
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+ from diffusers import DiffusionPipeline
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+ import torch
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+
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+ pipe = DiffusionPipeline.from_pretrained(
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+ "RunDiffusion/Juggernaut-Z-Image",
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+ subfolder="diffusers",
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+ torch_dtype=torch.bfloat16,
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+ ).to("cuda")
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+
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+ image = pipe(
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+ "a cinematic portrait, dramatic lighting",
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+ guidance_scale=6.0,
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+ num_inference_steps=35,
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+ ).images[0]
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+ image.save("output.png")
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+ ```
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+ Requires a version of `diffusers` that includes `ZImagePipeline` support (the format was exported against `diffusers` 0.37.1).
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  ## Links
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  Juggernaut Z is built on Z-Image Base — credit for the upstream base model belongs to the Z-Image team. This fine-tuned release is by **Team Juggernaut**, with training by **KandooAI**, published by **RunDiffusion**.
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+ ## License
 
 
 
 
 
 
 
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+ Released under the **Apache 2.0** license.