arielreplicate/scalable_diffusion_with_transformers 🔢❓ → 🖼️
About
Latent diffusion models, replacing the commonly-used U-Net backbone with a transformer that operates on latent patches
Example Output
Output
Performance Metrics
145.54s
Prediction Time
477.15s
Total Time
All Input Parameters
{
"cfg_scale": 4,
"class_name": "centipede",
"VAE_Decoder": "sd-vae-ft-mse",
"num_outputs": 4,
"DiT_resolution": "256x256",
"num_sampling_steps": 250
}
Input Parameters
- cfg_scale
- class_name
- Which ImageNet class to generate
- VAE_Decoder
- decoder type
- num_outputs
- How many outputs
- DiT_resolution
- Output image size
- num_sampling_steps
- Number of denoising steps
Output Schema
Output
Example Execution Logs
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Version Details
- Version ID
a11f7289b60685a4e48a0b09e41d091e27c2beb447877bc2117bfd6f9781c193- Version Created
- December 23, 2022