readme: ---
  license: creativeml-openrail-m
  tags:
  - pytorch
  - diffusers
  - stable-diffusion
  - text-to-image
  - diffusion-models-class
  - dreambooth-hackathon
  - wildcard
  ---
  
  # DreamBooth model of Kratos from God of War
  
  <img src="https://huggingface.co/matteopilotto/kratos-sd-v1-4-dreambooth/resolve/main/grid_hub_512px.png">
  
  This is a Stable Diffusion model fine-tuned on the person concept with DreamBooth. It can be used by adding the string `krts person` to any prompt.
  
  Check out the exampls below ☟ to see a few practical examples on how to use it.
  
  If you are curious to learn more about the training script, then I suggest you to visit the [report](https://wandb.ai/matt24/dreambooth-kratos/reports/Kratos-Dreambooth--VmlldzozMzQyMjQ4)📝 I created with Weights & Biases 🐝. 
  
  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!
  
  ## Description
  
  This is a Stable Diffusion model fine-tuned on [`matteopilotto/kratos`](https://huggingface.co/datasets/matteopilotto/kratos) dataset containing 10 images of **Kratos** 🪓 from **God of War** for the wildcard theme using [`CompVis/stable-diffusion-v1-4`](https://huggingface.co/CompVis/stable-diffusion-v1-4) pre-trained model.
  
  
  ## Example Output
  
  <img src="https://huggingface.co/matteopilotto/kratos-sd-v1-4-dreambooth/resolve/main/sample_outputs/245581956f83dc275e5d.png">
  
  **Prompt:** "An illustration of **krts** **person** punk playing electric guitar, tristan eaton, victo ngai, artgerm, rhads, ross draws"\
  **Negative prompt:** "low contrast, blurry, low resolution, warped"\
  **Resolution:** 512 x 512\
  **Guidance Scale:** 7\
  **Inference steps:** 50\
  **Seeds:** [556850, 459286, 768745, 594109]
  
  ---
  
  <img src="https://huggingface.co/matteopilotto/kratos-sd-v1-4-dreambooth/resolve/main/sample_outputs/4c4a87edbc0d5f03469a.png">
  
  **Prompt:** "a drawing of **krts** **person** wearing a Spider-man costume in the style of Marvel comics"\
  **Negative prompt:** "low contrast, blurry, low resolution, warped"\
  **Resolution:** 512 x 512\
  **Guidance Scale:** 7\
  **Inference steps:** 50\
  **Seeds:** [553766, 537908, 147395, 343240]
  
  ---
  
  <img src="https://huggingface.co/matteopilotto/kratos-sd-v1-4-dreambooth/resolve/main/sample_outputs/4dae428d30bddcc70967.png">
  
  **Prompt:** "an illustration of **krts** **person** sitting in a movie theater eating popcorn watching a movie, unreal engine, cozy indoor lighting, artstation, detailed, digital painting, cinematic, character design by mark ryden and pixar and hayao miyazaki, unreal 5, daz, hyperrealistic, octane render"\
  **Negative prompt:** "low contrast, blurry, low resolution, warped"\
  **Resolution:** 512 x 512\
  **Guidance Scale:** 7\
  **Inference steps:** 50\
  **Seeds:** [737986, 488711, 799063, 121111]
  
  ## Usage
  
  ```python
  import torch
  from diffusers import StableDiffusionPipeline
  
  # set device-agnostic code
  device = (
      'mps' if torch.backends.mps.is_available()
      else 'cuda' if torch.cuda.is_available()
      else 'cpu'
  )
  
  # load pre-trained model
  pretrained_ckpt = 'matteopilotto/kratos-sd-v1-4-dreambooth'
  pipeline = StableDiffusionPipeline.from_pretrained(pretrained_ckpt).to(device)
  
  # stable diffusion hyperparameters
  unique_token = 'krts'
  class_type = 'person'
  prompt = f'An illustration of {unique_token} {class_type} punk playing electric guitar, tristan eaton, victo ngai, artgerm, rhads, ross draws'
  negative_prompt = 'low contrast, blurry, low resolution, warped'
  guidance_scale = 7
  h = 512
  w = 512
  inference_steps = 50
  seed = 594109
  
  # set generator for reproducibility
  generator = torch.Generator(device=device).manual_seed(seed)
  
  # generate image
  image = pipeline(
      prompt,
      negative_prompt=negative_prompt,
      guidance_scale=guidance_scale,
      height=h,
      width=w,
      num_inference_steps=inference_steps,
      generator=generator
  ).images[0]
  ```
  