Instructions to use prithivMLmods/Qwen-Image-2.1-Amethyst-Theme with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use prithivMLmods/Qwen-Image-2.1-Amethyst-Theme with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Qwen/Qwen-Image-2.1", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("prithivMLmods/Qwen-Image-2.1-Amethyst-Theme") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
Qwen-Image-2.1-Amethyst-Theme
Qwen-Image-2.1-Amethyst-Theme is a LoRA adapter for Qwen-Image-2.1, designed to transform input images with an amethyst-inspired visual theme featuring rich purple tones, crystalline elements, violet hues, and an elegant mystical aesthetic. The adapter applies the amethyst-inspired appearance across subjects, objects, environments, and scenes while maintaining recognizable visual features, colors, spatial relationships, and important elements from the original image.
This is an experimental preview model. Results may vary depending on the input image, subject, composition, and visual complexity.
Download
Download the model files from the Files & versions tab:
Download Qwen-Image-2.1-Amethyst-Theme
Usage
Load the LoRA adapter with Qwen-Image-2.1 and provide an input image.
Use the trigger prompt:
Apply an amethyst theme to the image
For best results, use input images with clearly defined subjects, objects, and environments. The adapter can be applied to photographs, illustrations, characters, objects, and other visual compositions.
Base Model
This adapter is designed for:
License
Please refer to the license terms of the base model, Qwen-Image-2.1, and ensure compliance with its terms when using or redistributing this adapter.
Acknowledgements
This adapter was created by prithivMLmods and is built for use with Qwen-Image-2.1.
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