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  library_name: diffusers
 
 
 
 
 
 
 
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  ---
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- # Model Card for Model ID
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-
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- <!-- Provide a quick summary of what the model is/does. -->
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  ## Model Details
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  <!-- Provide a longer summary of what this model is. -->
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- This is the model card of a 🧨 diffusers model that has been pushed on the Hub. This model card has been automatically generated.
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-
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- - **Developed by:** [More Information Needed]
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- - **Funded by [optional]:** [More Information Needed]
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- - **Shared by [optional]:** [More Information Needed]
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- - **Model type:** [More Information Needed]
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- - **Language(s) (NLP):** [More Information Needed]
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- - **License:** [More Information Needed]
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- - **Finetuned from model [optional]:** [More Information Needed]
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  ### Model Sources [optional]
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  <!-- Provide the basic links for the model. -->
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- - **Repository:** [More Information Needed]
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- - **Paper [optional]:** [More Information Needed]
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- - **Demo [optional]:** [More Information Needed]
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  ## Uses
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- <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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- ### Direct Use
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- <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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- [More Information Needed]
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- ### Downstream Use [optional]
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- <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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- [More Information Needed]
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-
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- ### Out-of-Scope Use
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- <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
 
 
 
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- [More Information Needed]
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-
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- ## Bias, Risks, and Limitations
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- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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- [More Information Needed]
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- ### Recommendations
 
 
 
 
 
 
 
 
 
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- <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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- Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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- ## How to Get Started with the Model
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- Use the code below to get started with the model.
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  [More Information Needed]
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  ### Training Data
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- <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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  [More Information Needed]
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  ### Training Procedure
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- <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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- #### Preprocessing [optional]
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- [More Information Needed]
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  #### Training Hyperparameters
 
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  library_name: diffusers
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+ license: cc-by-nc-2.0
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+ base_model:
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+ - black-forest-labs/FLUX.1-Fill-dev
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+ pipeline_tag: image-to-image
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+ tags:
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+ - tryon
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+ - vto
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  ---
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+ # Model Card for CATVTON-Flux
 
 
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+ CATVTON-Flux is an advanced virtual try-on solution that combines CATVTON (Contrastive Appearance and Topology Virtual Try-On) with Flux fill inpainting model for realistic and accurate clothing transfer.
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  ## Model Details
 
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  <!-- Provide a longer summary of what this model is. -->
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+ - **Developed by:** [https://x.com/MrsZaaa]
 
 
 
 
 
 
 
 
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  ### Model Sources [optional]
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  <!-- Provide the basic links for the model. -->
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+ - **Repository:** [https://github.com/nftblackmagic/catvton-flux]
 
 
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  ## Uses
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+ The model is designed for virtual try-on applications, allowing users to visualize how different garments would look on a person. It can be used directly through command-line interface with the following parameters:
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ Input person image
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+ Person mask
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+ Garment image
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+ Random seed (optional)
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+ ## How to Get Started with the Model
 
 
 
 
 
 
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+ ```
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+ transformer = FluxTransformer2DModel.from_pretrained(
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+ "xiaozaa/catvton-flux-alpha",
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+ torch_dtype=torch.bfloat16
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+ )
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+ pipe = FluxFillPipeline.from_pretrained(
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+ "black-forest-labs/FLUX.1-dev",
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+ transformer=transformer,
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+ torch_dtype=torch.bfloat16
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+ ).to("cuda")
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+ ```
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  [More Information Needed]
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  ### Training Data
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+ VITON-HD
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  [More Information Needed]
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  ### Training Procedure
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+ Finetuning Flux1-dev-fill
 
 
 
 
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  #### Training Hyperparameters