Text-to-Image
Diffusers
TensorBoard
Safetensors
stable-diffusion
stable-diffusion-diffusers
custom-diffusion
diffusers-training
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Andy9310/saved_cat2_model", dtype=torch.bfloat16, device_map="cuda")
prompt = "a photo of <cat2>"
image = pipe(prompt).images[0]Custom Diffusion - Andy9310/saved_cat2_model
These are Custom Diffusion adaption weights for CompVis/stable-diffusion-v1-4. The weights were trained on a photo of using Custom Diffusion. You can find some example images in the following.
For more details on the training, please follow this link.
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 Andy9310/saved_cat2_model
Base model
CompVis/stable-diffusion-v1-4