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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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base_model: |
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- Qwen/Qwen-Image |
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pipeline_tag: text-to-image |
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tags: |
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- lora |
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- qwen |
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- qwen-image |
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- realism |
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- realism-lora |
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library_name: diffusers |
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--- |
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## LORA Qwen-Image example |
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Lora for [Qwen-Image](https://huggingface.co/Qwen/Qwen-Image) |
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**Realism** word required |
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# 📝 Updates |
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## August 13, 2025 - Realism v1.1 Release |
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- **Enhanced facial detail quality**: Improved fine-grained facial features and skin texture rendering |
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- **Better color reproduction**: More accurate and vibrant color representation across all scenes |
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- **Improved lighting and shadows for landscapes**: Enhanced natural lighting effects and shadow detail in outdoor scenes |
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- **Increased diversity across different ethnicities**: Better representation and quality for various racial and ethnic features |
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# 🧪 Usage |
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--- |
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### 🔧 Initialization |
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```python |
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from diffusers import DiffusionPipeline |
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import torch |
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model_name = "Qwen/Qwen-Image" |
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# Load the pipeline |
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if torch.cuda.is_available(): |
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torch_dtype = torch.bfloat16 |
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device = "cuda" |
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else: |
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torch_dtype = torch.float32 |
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device = "cpu" |
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pipe = DiffusionPipeline.from_pretrained(model_name, torch_dtype=torch_dtype) |
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pipe = pipe.to(device) |
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``` |
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### 🔌 Load LoRA Weights |
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```python |
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# Load LoRA weights |
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pipe.load_lora_weights('flymy_realism.safetensors', adapter_name="lora") |
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``` |
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### 🎨 Generate Image with lora trained on person |
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```python |
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prompt = '''Super Realism portrait of a teenager woman of African descent, serene calmness, arms crossed, illuminated by dramatic studio lighting, sunlit park in the background, adorned with delicate jewelry, three-quarter view, sun-kissed skin with natural imperfections, loose shoulder-length curls, slightly squinting eyes, environmental street portrait with text "FLYMY AI" on t-shirt.''' |
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negative_prompt = " " |
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image = pipe( |
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prompt=prompt, |
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negative_prompt=negative_prompt, |
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width=1024, |
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height=1024, |
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num_inference_steps=50, |
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true_cfg_scale=5, |
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generator=torch.Generator(device="cuda").manual_seed(346346) |
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) |
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# Display the image (in Jupyter or save to file) |
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image.show() |
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# or |
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image.save("output.png") |
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``` |
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### 🖼️ Sample Output |
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## 🎛️ Using with ComfyUI |
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We provide a ready-to-use ComfyUI workflow that works with our trained LoRA models. Follow these steps to set up and use the workflow: |
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### Setup Instructions |
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1. **Download the latest ComfyUI**: |
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- Visit the [ComfyUI GitHub repository](https://github.com/comfyanonymous/ComfyUI) |
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- Clone or download the latest version |
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2. **Install ComfyUI**: |
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- Follow the installation instructions from the [ComfyUI repository](https://github.com/comfyanonymous/ComfyUI?tab=readme-ov-file#installing) |
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- Make sure all dependencies are properly installed |
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3. **Download Qwen-Image model weights**: |
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- Go to [Qwen-Image ComfyUI weights](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/tree/main) |
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- Download all the model files |
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4. **Place Qwen-Image weights in ComfyUI**: |
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- Copy the downloaded Qwen-Image model files to the appropriate folders in `ComfyUI/models/` |
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- Follow the folder structure as specified in the model repository |
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5. **Download our pre-trained LoRA weights**: |
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- Visit [flymy-ai/qwen-image-lora](https://huggingface.co/flymy-ai/qwen-image-lora) |
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- Download the LoRA `.safetensors` files |
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6. **Place LoRA weights in ComfyUI**: |
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- Copy the LoRA file `flymy-ai/qwen-image-lora/pytorch_lora_weights.safetensors` to `ComfyUI/models/loras/` |
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7. **Load the workflow**: |
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- Open ComfyUI in your browser |
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- Load the workflow file `qwen_image_lora_example.json` located in this repository |
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- The workflow is pre-configured to work with our LoRA models |
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### Workflow Features |
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- ✅ Pre-configured for Qwen-Image + LoRA inference |
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- ✅ Optimized settings for best quality output |
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- ✅ Easy prompt and parameter adjustment |
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- ✅ Compatible with all our trained LoRA models |
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The ComfyUI workflow provides a user-friendly interface for generating images with our trained LoRA models without needing to write Python code. |
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### 🖼️ Workflow Screenshot |
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## 📊 Side-by-Side Comparisons |
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Below are comparison images showing the improvements of our LoRA model across different scenarios: |
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### Mountain Landscape |
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**Prompt**: *"realism, mountain landscape at golden hour, low sun grazing alpine meadows, crisp ridgelines, thin mist in valley, high dynamic range sky, 24mm f/8, ISO 100, tripod, ultra-sharp foreground grass, micro-contrast on rocks"* |
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### Rainy Night City Scene |
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**Prompt**: *"realism, rainy night city scene with neon reflections, person holding a transparent umbrella, water droplets sharp on umbrella surface, shallow DOF, 55mm f/1.8, ISO 1600, blue and magenta neon, storefront sign reads "OPEN 24/7""* |
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### Athletic Motion |
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**Prompt**: *"realism, athlete mid-sprint on track, strong sunlight, backlit dust particles, frozen motion at 1/2000s, 200mm f/2.8, ISO 400, muscle definition and sweat droplets detailed, stadium banner says "FINALS""* |
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### Corporate Portrait |
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**Prompt**: *"realism, corporate headshot of a CTO in glass-walled office, city skyline bokeh, balanced key/fill lighting, 85mm f/2, ISO 100, crisp lapel and hair detail, subtle reflection on glasses"* |
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## 🤝 Support |
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If you have questions or suggestions, join our community: |
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- 🌐 [FlyMy.AI](https://flymy.ai) |
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- 💬 [Discord Community](https://discord.com/invite/t6hPBpSebw) |
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- 🐦 [Follow us on X](https://x.com/flymyai) |
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- 💼 [Connect on LinkedIn](https://linkedin.com/company/flymyai) |
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- 📧 [Support](mailto:[email protected]) |
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**⭐ Don't forget to star the repository if you like it!** |
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--- |
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license: apache-2.0 |
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--- |