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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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  ![4](images/5_compressed.png)
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  <center><i>an air conditioner hanging on the bedroom wall</i></center>
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- # How to Use
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- Dowanlod two python filespipeline_sd3_controlnet_inpainting.py and controlnet_sd3.py can be found in the root directory of the current repo.
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- We will merge this Feature to official Diffusers.
 
 
 
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  ``` python
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  from diffusers.utils import load_image, check_min_version
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  ## Limitation
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- Due to the fact that only 1024*1024 pixel resolution was used during the training phase, the inference performs best at this size, with other sizes yielding suboptimal results. We will initiate multi-resolution training in the future, and at that time, we will open-source the new weights.
 
 
 
 
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+ license: other
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  language:
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  - en
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  pipeline_tag: text-to-image
 
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  ![4](images/5_compressed.png)
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  <center><i>an air conditioner hanging on the bedroom wall</i></center>
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+ # Using with Diffusers
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+ Step1Make sure you upgrade to the latest version of diffusers(>=0.29.2): pip install -U diffusers.
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+ Step2: Download the two required Python files(pipeline_sd3_controlnet_inpainting.py and controlnet_sd3.py) from either the current repo or from (GitHub)[https://github.com/JPlin/SD3-Controlnet-Inpainting].
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+ (We will merge this Feature to official Diffusers.)
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+
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+ Step3: And then you can run demo.py or following:
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  ``` python
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  from diffusers.utils import load_image, check_min_version
 
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  ## Limitation
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+ Due to the fact that only 1024*1024 pixel resolution was used during the training phase, the inference performs best at this size, with other sizes yielding suboptimal results. We will initiate multi-resolution training in the future, and at that time, we will open-source the new weights.
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+
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+ ## LICENSE
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+ The model is based on SD3 finetuning; therefore, the license follows the original (SD3 license)[https://huggingface.co/stabilityai/stable-diffusion-3-medium#license].