tstramer/arcane-diffusion 🔢❓📝 → 🖼️
About

Example Output
Prompt:
"harry potter, arcane style, intricate highly detailed digital painting artstation concept art smooth sharp focus illustration Unreal Engine 5 8K"
Output

Performance Metrics
16.48s
Prediction Time
163.22s
Total Time
All Input Parameters
{ "width": 512, "height": 512, "prompt": "harry potter, arcane style, intricate highly detailed digital painting artstation concept art smooth sharp focus illustration Unreal Engine 5 8K", "scheduler": "K-LMS", "num_outputs": 1, "guidance_scale": 7.5, "prompt_strength": 0.8, "num_inference_steps": "150" }
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: 60774 0%| | 0/150 [00:00<?, ?it/s] 1%| | 1/150 [00:02<05:26, 2.19s/it] 2%|▏ | 3/150 [00:02<01:31, 1.60it/s] 3%|▎ | 5/150 [00:02<00:49, 2.93it/s] 5%|▍ | 7/150 [00:02<00:32, 4.38it/s] 6%|▌ | 9/150 [00:02<00:24, 5.86it/s] 7%|▋ | 11/150 [00:02<00:19, 7.28it/s] 9%|▊ | 13/150 [00:03<00:15, 8.57it/s] 10%|█ | 15/150 [00:03<00:13, 9.69it/s] 11%|█▏ | 17/150 [00:03<00:12, 10.63it/s] 13%|█▎ | 19/150 [00:03<00:11, 11.39it/s] 14%|█▍ | 21/150 [00:03<00:10, 11.92it/s] 15%|█▌ | 23/150 [00:03<00:10, 12.35it/s] 17%|█▋ | 25/150 [00:03<00:09, 12.73it/s] 18%|█▊ | 27/150 [00:04<00:09, 12.88it/s] 19%|█▉ | 29/150 [00:04<00:09, 12.68it/s] 21%|██ | 31/150 [00:04<00:09, 12.99it/s] 22%|██▏ | 33/150 [00:04<00:08, 13.24it/s] 23%|██▎ | 35/150 [00:04<00:08, 13.29it/s] 25%|██▍ | 37/150 [00:04<00:08, 13.46it/s] 26%|██▌ | 39/150 [00:05<00:08, 13.51it/s] 27%|██▋ | 41/150 [00:05<00:08, 13.52it/s] 29%|██▊ | 43/150 [00:05<00:07, 13.57it/s] 30%|███ | 45/150 [00:05<00:07, 13.65it/s] 31%|███▏ | 47/150 [00:05<00:07, 13.64it/s] 33%|███▎ | 49/150 [00:05<00:07, 13.54it/s] 34%|███▍ | 51/150 [00:05<00:07, 13.58it/s] 35%|███▌ | 53/150 [00:06<00:07, 13.66it/s] 37%|███▋ | 55/150 [00:06<00:06, 13.72it/s] 38%|███▊ | 57/150 [00:06<00:07, 12.92it/s] 39%|███▉ | 59/150 [00:06<00:07, 12.22it/s] 41%|████ | 61/150 [00:06<00:07, 12.41it/s] 42%|████▏ | 63/150 [00:06<00:06, 12.61it/s] 43%|████▎ | 65/150 [00:07<00:06, 12.90it/s] 45%|████▍ | 67/150 [00:07<00:06, 13.17it/s] 46%|████▌ | 69/150 [00:07<00:06, 13.32it/s] 47%|████▋ | 71/150 [00:07<00:05, 13.50it/s] 49%|████▊ | 73/150 [00:07<00:05, 13.61it/s] 50%|█████ | 75/150 [00:07<00:05, 13.47it/s] 51%|█████▏ | 77/150 [00:07<00:05, 13.46it/s] 53%|█████▎ | 79/150 [00:08<00:05, 13.55it/s] 54%|█████▍ | 81/150 [00:08<00:05, 13.61it/s] 55%|█████▌ | 83/150 [00:08<00:04, 13.61it/s] 57%|█████▋ | 85/150 [00:08<00:04, 13.62it/s] 58%|█████▊ | 87/150 [00:08<00:04, 13.67it/s] 59%|█████▉ | 89/150 [00:08<00:04, 13.54it/s] 61%|██████ | 91/150 [00:08<00:04, 13.47it/s] 62%|██████▏ | 93/150 [00:09<00:04, 13.56it/s] 63%|██████▎ | 95/150 [00:09<00:04, 13.48it/s] 65%|██████▍ | 97/150 [00:09<00:03, 13.48it/s] 66%|██████▌ | 99/150 [00:09<00:03, 13.60it/s] 67%|██████▋ | 101/150 [00:09<00:03, 13.63it/s] 69%|██████▊ | 103/150 [00:09<00:03, 13.64it/s] 70%|███████ | 105/150 [00:09<00:03, 13.56it/s] 71%|███████▏ | 107/150 [00:10<00:03, 13.57it/s] 73%|███████▎ | 109/150 [00:10<00:03, 13.55it/s] 74%|███████▍ | 111/150 [00:10<00:02, 13.64it/s] 75%|███████▌ | 113/150 [00:10<00:02, 13.70it/s] 77%|███████▋ | 115/150 [00:10<00:02, 13.57it/s] 78%|███████▊ | 117/150 [00:10<00:02, 13.72it/s] 79%|███████▉ | 119/150 [00:10<00:02, 13.82it/s] 81%|████████ | 121/150 [00:11<00:02, 13.86it/s] 82%|████████▏ | 123/150 [00:11<00:01, 13.88it/s] 83%|████████▎ | 125/150 [00:11<00:01, 13.90it/s] 85%|████████▍ | 127/150 [00:11<00:01, 13.93it/s] 86%|████████▌ | 129/150 [00:11<00:01, 13.80it/s] 87%|████████▋ | 131/150 [00:11<00:01, 13.78it/s] 89%|████████▊ | 133/150 [00:11<00:01, 13.80it/s] 90%|█████████ | 135/150 [00:12<00:01, 13.86it/s] 91%|█████████▏| 137/150 [00:12<00:00, 13.88it/s] 93%|█████████▎| 139/150 [00:12<00:00, 13.87it/s] 94%|█████████▍| 141/150 [00:12<00:00, 13.87it/s] 95%|█████████▌| 143/150 [00:12<00:00, 13.61it/s] 97%|█████████▋| 145/150 [00:12<00:00, 13.68it/s] 98%|█████████▊| 147/150 [00:13<00:00, 13.50it/s] 99%|█████████▉| 149/150 [00:13<00:00, 13.62it/s] 100%|██████████| 150/150 [00:13<00:00, 11.34it/s]
Version Details
- Version ID
4cbb3f91f9ba049151efb8922fdecc6703d419ea682b87ff94c5876addabfb19
- Version Created
- January 3, 2023