import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("plasmo/food-crit", dtype=torch.bfloat16, device_map="cuda")
prompt = "food_crit "
image = pipe(prompt).images[0]Jak's Creepy Critter Pack for Stable Diffusion
Trained using TheLastBen Dreambooth colab notebook, using 95 training images, 5000 training steps.
Use Prompt: "food_crit" in the beginning of your prompt followed by a food. No major prompt-crafting needed.
Thanks to /u/Jak_TheAI_Artist for supplying training images!
Sample pictures of this concept:
prompt: "food_crit, spaghetti and meatballs"
prompt: "food_crit, snowcone" 
prompt: "food_crit, cola cola, vibrant colors"
Steps: 27, Sampler: Euler a, CFG scale: 6, Seed: 1195328763
prompt: "shiny ceramic 3d painting, (mens's shoe creature) gum stuck to sole, high detail render, vibrant, cinematic lighting"
Negative prompt: painting, photoshop, illustration, blurry, dull, drawing
Steps: 40, Sampler: Euler a, CFG scale: 10, Seed: 1018346393
Prompt: "melting trippy zombie muscle car, smoking, with big eyes, hyperrealistic, intricate detail, high detail render, vibrant, cinematic lighting, shiny, ceramic, reflections"
Negative prompt: "painting, photoshop, illustration, blurry, dull"
Steps: 40, Sampler: Euler a, CFG scale: 10, Seed: 3713218290, Size: 960x512, Model hash: d9aa872b
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