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("ButterChicken98/pv_smtssm_v3", dtype=torch.bfloat16, device_map="cuda")
prompt = "A photo of a leaf infested with spider mites, showing tiny webbing and yellow spots. hd, 4k"
image = pipe(prompt).images[0]DreamBooth - ButterChicken98/pv_smtssm_v3
This is a dreambooth model derived from stable-diffusion-v1-5/stable-diffusion-v1-5. The weights were trained on A photo of a leaf infested with spider mites, showing tiny webbing and yellow spots. hd, 4k using DreamBooth. You can find some example images in the following.
DreamBooth for the text encoder was enabled: True.
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 ButterChicken98/pv_smtssm_v3
Base model
stable-diffusion-v1-5/stable-diffusion-v1-5