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nroggendorff/nebulae
nebulae is a unconditional image generation model from nroggendorff. Use it for the unconditional image generation task on the model card, and read the license before you ship it in a product. It is set up for diffusers. The card lists the license as mit.
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.
Downloads · 30 days
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From the Hugging Face model README
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.

from diffusers import DiffusionPipeline
pipeline = DiffusionPipeline.from_pretrained("nroggendorff/nebulae")
pipe = pipeline.to("cuda")
image = pipe().images[0]
image.save("nebula.png")
train_batch_size: 16eval_batch_size: 16num_epochs: 50gradient_accumulation_steps: 1learning_rate: 1e-4lr_warmup_steps: 500mixed_precision: "fp16"eval_metric: "mean_squared_error"This model card was written by Noa Roggendorff and is based on the Stable Diffusion v1-5 Model Card.