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nroggendorff/
cats

Name: cats
Availability: InStock

unconditional-image-generation

mit

DDPMPipeline

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Cursedte kitty cats Model Card

DDPMCats is a latent noise-to-image diffusion model capable of generating images of cats. For more information about how Stable Diffusion functions, please have a look at 🤗's Stable Diffusion blog.

You can use this with the 🧨Diffusers library from Hugging Face.

Diffusers

from diffusers import DiffusionPipeline

pipeline = DiffusionPipeline.from_pretrained("nroggendorff/cats")
pipe = pipeline.to("cuda")

image = pipe().images[0]  

image.save("cat.png")

Model Details

train_batch_size: 16
eval_batch_size: 16
num_epochs: 50
gradient_accumulation_steps: 1
learning_rate: 1e-4
lr_warmup_steps: 500
mixed_precision: "fp16"
eval_metric: "mean_squared_error"

Bias

This model may exhibit biases due to its training data. It will not display images of abused or sick cats, as it prioritizes the well-being of animals.

Limitations

The model does not achieve perfect photorealism
The model cannot render legible text
The model was trained on a medium-to-large-scale dataset: huggan/few-shot-cat

Developed by

Noa Linden Roggendorff

This model card was written by Noa Roggendorff and is based on the Stable Diffusion v1-5 Model Card.