--- license: creativeml-openrail-m tags: - pytorch - diffusers - stable-diffusion - text-to-image - diffusion-models-class - dreambooth-hackathon - wildcard widget: - text: a pkblz ball in the middle of a miniature jungle - text: a photo of a spectral ornate pkblz ball, trending on artstation, realistic - text: a colored pencil sketch of a pkblz ball --- # The Pokeball Machine The **Pokeball Machine** is a Dreambooth model for the `pokeball` concept (represented by the `pkblz` identifier). It applies to the *wildcard* theme. It is fine-tuned from `CompVis/stable-diffusion-v1-4` checkpoint on a small dataset of pokeball images (i.e., images of the red-white original pokeball). It can be used by modifying the `instance_prompt`: **a pkblz ball in the middle of a miniature jungle** This model was created as part of the DreamBooth Hackathon 🔥. Visit the [organisation page](https://huggingface.co/dreambooth-hackathon) for instructions on how to take part! #### Fine-Tuning Details - Number of training images: 31 - Learning rate: 2e-06 - Training steps: 800 - Guidance Scale: 10 - Inference Steps: 50-75 #### Output Examples
a blueprint photo of a pkblz ball a photo of a cybernetic pkblz ball, wide shot a photo of a pkblz ball in the style vintage disney
a photo of a mosaic pkblz ball lying in an antique temple a photo of a detailed ornate pkblz ball a pkblz ball underwater
a pkblz ball in the middle of a miniature jungle a pkblz ball underwater a mystic pkblz ball, trending on artstation
a pkblz ball underwater, trending on artstation a wooden pkblz ball a pkblz ball hovering over a pond
a pkblz ball on a sunny tropical beach a steampunk pkblz ball, trending on artstation a colored pencil sketch of a pkblz ball
a photo of a spectral ornate pkblz ball, trending on artstation, realistic a sunset photo of a pkblz ball a watercolor photo of a pkblz ball
## Usage ```python from diffusers import StableDiffusionPipeline import torch device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu') pipeline = StableDiffusionPipeline.from_pretrained('simonschoe/pokeball-machine').to(device) prompt = "a pkblz ball in the middle of a miniature jungle" image = pipeline( prompt, num_inference_steps=50, guidance_scale=10, num_images_per_prompt=1 ).images[0] image ```