tstramer/mo-di-diffusion 🔢❓📝 → 🖼️
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Example Output
Prompt:
"simba from lion king, modern disney style"
Output

Performance Metrics
14.37s
Prediction Time
167.01s
Total Time
All Input Parameters
{ "seed": 5, "width": 512, "height": 512, "prompt": "simba from lion king, modern disney style", "scheduler": "K-LMS", "num_outputs": 1, "guidance_scale": 7.5, "prompt_strength": 0.8, "num_inference_steps": "117" }
Input Parameters
- seed
- Random seed. Leave blank to randomize the seed
- width
- Width of output image. Maximum size is 1024x768 or 768x1024 because of memory limits
- height
- Height of output image. Maximum size is 1024x768 or 768x1024 because of memory limits
- prompt
- Input prompt
- scheduler
- Choose a scheduler.
- num_outputs
- Number of images to output.
- guidance_scale
- Scale for classifier-free guidance
- negative_prompt
- Specify things to not see in the output
- prompt_strength
- Prompt strength when using init image. 1.0 corresponds to full destruction of information in init image
- num_inference_steps
- Number of denoising steps
Output Schema
Output
Example Execution Logs
Using seed: 5 0%| | 0/117 [00:00<?, ?it/s] 1%| | 1/117 [00:02<04:24, 2.28s/it] 3%|▎ | 3/117 [00:02<01:13, 1.55it/s] 4%|▍ | 5/117 [00:02<00:39, 2.84it/s] 6%|▌ | 7/117 [00:02<00:25, 4.26it/s] 8%|▊ | 9/117 [00:02<00:19, 5.64it/s] 9%|▉ | 11/117 [00:03<00:14, 7.08it/s] 11%|█ | 13/117 [00:03<00:12, 8.46it/s] 13%|█▎ | 15/117 [00:03<00:10, 9.66it/s] 15%|█▍ | 17/117 [00:03<00:09, 10.66it/s] 16%|█▌ | 19/117 [00:03<00:08, 11.13it/s] 18%|█▊ | 21/117 [00:03<00:08, 11.72it/s] 20%|█▉ | 23/117 [00:03<00:07, 12.15it/s] 21%|██▏ | 25/117 [00:04<00:07, 12.46it/s] 23%|██▎ | 27/117 [00:04<00:07, 12.72it/s] 25%|██▍ | 29/117 [00:04<00:06, 12.91it/s] 26%|██▋ | 31/117 [00:04<00:06, 13.02it/s] 28%|██▊ | 33/117 [00:04<00:06, 13.13it/s] 30%|██▉ | 35/117 [00:04<00:06, 13.18it/s] 32%|███▏ | 37/117 [00:04<00:06, 13.23it/s] 33%|███▎ | 39/117 [00:05<00:05, 13.32it/s] 35%|███▌ | 41/117 [00:05<00:05, 13.47it/s] 37%|███▋ | 43/117 [00:05<00:05, 13.57it/s] 38%|███▊ | 45/117 [00:05<00:05, 13.63it/s] 40%|████ | 47/117 [00:05<00:05, 13.57it/s] 42%|████▏ | 49/117 [00:05<00:04, 13.60it/s] 44%|████▎ | 51/117 [00:06<00:04, 13.61it/s] 45%|████▌ | 53/117 [00:06<00:04, 13.66it/s] 47%|████▋ | 55/117 [00:06<00:04, 13.64it/s] 49%|████▊ | 57/117 [00:06<00:04, 13.57it/s] 50%|█████ | 59/117 [00:06<00:04, 13.57it/s] 52%|█████▏ | 61/117 [00:06<00:04, 13.56it/s] 54%|█████▍ | 63/117 [00:06<00:03, 13.53it/s] 56%|█████▌ | 65/117 [00:07<00:03, 13.46it/s] 57%|█████▋ | 67/117 [00:07<00:03, 13.34it/s] 59%|█████▉ | 69/117 [00:07<00:03, 13.42it/s] 61%|██████ | 71/117 [00:07<00:03, 13.40it/s] 62%|██████▏ | 73/117 [00:07<00:03, 13.51it/s] 64%|██████▍ | 75/117 [00:07<00:03, 13.53it/s] 66%|██████▌ | 77/117 [00:07<00:02, 13.55it/s] 68%|██████▊ | 79/117 [00:08<00:02, 13.62it/s] 69%|██████▉ | 81/117 [00:08<00:02, 13.60it/s] 71%|███████ | 83/117 [00:08<00:02, 13.68it/s] 73%|███████▎ | 85/117 [00:08<00:02, 13.78it/s] 74%|███████▍ | 87/117 [00:08<00:02, 13.83it/s] 76%|███████▌ | 89/117 [00:08<00:02, 13.86it/s] 78%|███████▊ | 91/117 [00:08<00:01, 13.75it/s] 79%|███████▉ | 93/117 [00:09<00:01, 13.75it/s] 81%|████████ | 95/117 [00:09<00:01, 13.77it/s] 83%|████████▎ | 97/117 [00:09<00:01, 13.77it/s] 85%|████████▍ | 99/117 [00:09<00:01, 13.75it/s] 86%|████████▋ | 101/117 [00:09<00:01, 13.68it/s] 88%|████████▊ | 103/117 [00:09<00:01, 13.54it/s] 90%|████████▉ | 105/117 [00:09<00:00, 13.53it/s] 91%|█████████▏| 107/117 [00:10<00:00, 13.60it/s] 93%|█████████▎| 109/117 [00:10<00:00, 13.47it/s] 95%|█████████▍| 111/117 [00:10<00:00, 13.53it/s] 97%|█████████▋| 113/117 [00:10<00:00, 13.64it/s] 98%|█████████▊| 115/117 [00:10<00:00, 13.66it/s] 100%|██████████| 117/117 [00:10<00:00, 13.66it/s] 100%|██████████| 117/117 [00:10<00:00, 10.77it/s]
Version Details
- Version ID
4cee26e8ef4979d7faa7118eb938b258cea03b2b99f23796248e4d93ba5c4e25
- Version Created
- January 4, 2023