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obama
nroggendorff/obama
obama 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.
DDPMObama is a latent noise-to-image diffusion model capable of generating images of obama. For more information about how Stable Diffusion functions, please have a look at 🤗's Stable Diffusion blog.
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At a glance
- Task
- Unconditional Image Generation
- Library
- diffusers
- License
- mit
- Access
- Public
- Created
- Apr 7, 2024
- Updated
- Apr 9, 2024
- SHA
- b7e02904
Spaces
Model card
From the Hugging Face model README
Obama Model Card
DDPMObama is a latent noise-to-image diffusion model capable of generating images of obama. 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/obama")
pipe = pipeline.to("cuda")
image = pipe().images[0]
image.save("obama.png")
Model Details
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"
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: few-shot-obama
Developed by
- Noa Linden Roggendorff
This model card was written by Noa Roggendorff and is based on the Stable Diffusion v1-5 Model Card.
- Task
- Unconditional Image Generation
- Library
- diffusers
- License
- mit
- Created
- Apr 7, 2024
- Updated
- Apr 9, 2024