Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
dreambooth
diffusers-training
stable-diffusion
stable-diffusion-diffusers
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("aang77/disater", dtype=torch.bfloat16, device_map="cuda")
prompt = "A photo of buildings collapsed due to an earthquake, with debris and rubble scattered across the ground, cracked walls, and fallen structures, as dust clouds rise from the destruction."
image = pipe(prompt).images[0]DreamBooth - aang77/disater
This is a dreambooth model derived from stabilityai/stable-diffusion-2. The weights were trained on A photo of buildings collapsed due to an earthquake, with debris and rubble scattered across the ground, cracked walls, and fallen structures, as dust clouds rise from the destruction. using DreamBooth. You can find some example images in the following.
DreamBooth for the text encoder was enabled: False.
Intended uses & limitations
How to use
# TODO: add an example code snippet for running this diffusion pipeline
Limitations and bias
[TODO: provide examples of latent issues and potential remediations]
Training details
[TODO: describe the data used to train the model]
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Model tree for aang77/disater
Base model
stabilityai/stable-diffusion-2