Update README with Zen branding
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README.md
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---
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pipeline_tag: text-to-image
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tags:
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---
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# Zen3 Image Dev
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**
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##
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| Property | Value |
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|----------|-------|
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## API Access
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```bash
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curl https://api.hanzo.ai/v1/chat/completions \
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-H "Authorization: Bearer $HANZO_API_KEY" \
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-H "Content-Type: application/json" \
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-d '{"model": "zen3-image-dev", "messages": [{"role": "user", "content": "Hello"}]}'
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```
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---
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license: mit
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language:
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- en
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pipeline_tag: text-to-image
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tags:
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- diffusers
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- text-to-image
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- image-generation
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- zen
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- hanzo
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library_name: diffusers
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# Zen3 Image Dev
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**Zen3 Image Dev** is a high-fidelity text-to-image generation model developed by [Hanzo AI](https://hanzo.ai) as part of the Zen model family. It produces photorealistic and artistically detailed images with exceptional prompt adherence.
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## Overview
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Zen3 Image Dev prioritizes image quality and prompt fidelity over speed. It excels at generating detailed, coherent images across a wide range of styles and subjects, making it the premium choice for quality-critical applications.
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### Key Features
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- **Exceptional image quality**: State-of-the-art visual fidelity
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- **Strong prompt adherence**: Accurately renders complex descriptions
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- **Versatile style range**: Photorealism, illustration, 3D, and more
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- **High resolution**: Native 1024x1024 with support for other aspect ratios
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## Usage
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```python
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from diffusers import DiffusionPipeline
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import torch
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pipe = DiffusionPipeline.from_pretrained(
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"zenlm/zen3-image-dev",
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torch_dtype=torch.bfloat16
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)
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pipe.to("cuda")
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image = pipe(
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"A majestic mountain landscape reflected in a crystal clear alpine lake at golden hour",
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num_inference_steps=28,
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guidance_scale=5.0,
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height=1024,
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width=1024,
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).images[0]
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image.save("output.png")
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```
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## Model Details
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| Property | Value |
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|----------|-------|
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| Architecture | Diffusion Transformer |
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| Precision | bfloat16 |
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| License | MIT |
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| Output Resolution | Up to 1024x1024 |
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| Inference Steps | 20-50 (recommended: 28) |
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## Intended Use
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- High-quality image generation
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- Creative and artistic production
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- Marketing and design assets
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- Research and experimentation
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## Limitations
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- Slower inference compared to Zen3 Image Fast
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- Requires more VRAM for optimal quality
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- Text rendering in generated images may be imperfect
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- Complex multi-subject scenes may require prompt refinement
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## Citation
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```bibtex
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@misc{zen3-image-dev,
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title={Zen3 Image Dev: High-Fidelity Text-to-Image Generation},
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author={Hanzo AI},
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year={2025},
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url={https://huggingface.co/zenlm/zen3-image-dev}
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}
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```
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## Links
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- [Zen Model Family](https://huggingface.co/zenlm)
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- [Hanzo AI](https://hanzo.ai)
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