nebulae

Nebulae Model Card

DDPMNebula is a latent noise-to-image diffusion model capable of generating images of nebulas. 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/nebulae")
pipe = pipeline.to("cuda")

image = pipe().images[0]  

image.save("nebula.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"

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: Nebulae

Developed by

• Noa Linden Roggendorff

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