| --- |
| license: apache-2.0 |
| --- |
| # Glass Sculpture - Kontext Image Editing LoRA |
|
|
| ## Model Introduction |
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| This LoRA model is trained based on the [Kontext](https://www.modelscope.cn/models/black-forest-labs/FLUX.1-Kontext-dev) model and [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio). After using this model, you can input the instruction `Transform into a glass sculpture.` to transform the main subject in an image into a sparkling glass sculpture. |
|
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| ## Model Results |
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| ||Example 1|Example 2|Example 3| |
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| |Original|||| |
| |Generated|||| |
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| ||Example 4|Example 5|Example 6| |
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| |Original|||| |
| |Generated|||| |
|
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| ## Usage Instructions |
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| This model is trained using the [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio/tree/main/examples/flux) framework. Please install it first: |
|
|
| ``` |
| git clone https://github.com/modelscope/DiffSynth-Studio.git |
| cd DiffSynth-Studio |
| pip install -e . |
| ``` |
|
|
| ```python |
| import torch |
| from diffsynth.pipelines.flux_image_new import FluxImagePipeline, ModelConfig |
| from PIL import Image |
| from modelscope import snapshot_download |
| |
| snapshot_download("DiffSynth-Studio/FLUX.1-Kontext-dev-lora-blingbling", cache_dir="./models") |
| pipe = FluxImagePipeline.from_pretrained( |
| torch_dtype=torch.bfloat16, |
| device="cuda", |
| model_configs=[ |
| ModelConfig(model_id="black-forest-labs/FLUX.1-Kontext-dev", origin_file_pattern="flux1-kontext-dev.safetensors"), |
| ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="text_encoder/model.safetensors"), |
| ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="text_encoder_2/"), |
| ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="ae.safetensors"), |
| ], |
| ) |
| pipe.load_lora(pipe.dit, "models/DiffSynth-Studio/FLUX.1-Kontext-dev-lora-blingbling/model.safetensors", alpha=1) |
| |
| image = Image.open("your_image.jpg") |
| image = pipe( |
| prompt="Transform into a glass sculpture.", |
| kontext_images=image, |
| embedded_guidance=2.5, |
| seed=0, |
| ) |
| image.save("output.jpg") |
| ``` |