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@@ -7,31 +7,33 @@ datasets: Qilex/private_guys
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  metrics: []
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  ---
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- <!-- This model card has been generated automatically according to the information the training script had access to. You
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- should probably proofread and complete it, then remove this comment. -->
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  # VirtualPetDiffusion2
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  ## Model description
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  This diffusion model is trained with the [🤗 Diffusers](https://github.com/huggingface/diffusers) library
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- on the `Qilex/private_guys` dataset.
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  ## Intended uses & limitations
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  #### How to use
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  ```python
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- # TODO: add an example code snippet for running this diffusion pipeline
 
 
 
 
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  ```
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- #### Limitations and bias
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-
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- [TODO: provide examples of latent issues and potential remediations]
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-
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  ## Training data
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- [TODO: describe the data used to train the model]
 
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  ### Training hyperparameters
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  metrics: []
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  ---
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  # VirtualPetDiffusion2
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  ## Model description
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  This diffusion model is trained with the [🤗 Diffusers](https://github.com/huggingface/diffusers) library
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+ on a dataset of roughly 8,000 virtual pet thumbnail images.
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  ## Intended uses & limitations
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+ This model can be used to generate small (128x128) virtual pet-like thumbnails.
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+ The pets are generally somewhat abstract.
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+
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  #### How to use
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  ```python
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+ from diffusers import DiffusionPipeline
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+ pipeline = DiffusionPipeline.from_pretrained("Qilex/VirtualPetDiffusion2")
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+ image = pipeline()["sample"][0]
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+ #this line only works in jupyter
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+ display(image)
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  ```
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  ## Training data
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+ This model was trained on roughly 8,000 virtual pet thumbnail images (80x80px).
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+ The data was randomly flipped, rotated, and perspected using torchvision transforms to prevent some of the issues from the first VirtualPetDiffusion.
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  ### Training hyperparameters
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