fofr/sdxl-tron 🖼️🔢📝❓✓ → 🖼️
About
A fine-tuned SDXL lora based on Tron Legacy
Example Output
Prompt:
"A futuristic close-up portrait photo in the style of TRN"
Output
Performance Metrics
14.73s
Prediction Time
14.69s
Total Time
All Input Parameters
{
"width": 1024,
"height": 1024,
"prompt": "A futuristic close-up portrait photo in the style of TRN",
"refine": "expert_ensemble_refiner",
"scheduler": "K_EULER",
"lora_scale": 0.6,
"num_outputs": 1,
"guidance_scale": 7.5,
"apply_watermark": false,
"high_noise_frac": 0.9,
"negative_prompt": "ugly, broken, disfigured, people",
"prompt_strength": 0.8,
"num_inference_steps": 50
}
Input Parameters
- mask
- Input mask for inpaint mode. Black areas will be preserved, white areas will be inpainted.
- seed
- Random seed. Leave blank to randomize the seed
- image
- Input image for img2img or inpaint mode
- width
- Width of output image
- height
- Height of output image
- prompt
- Input prompt
- refine
- Which refine style to use
- scheduler
- scheduler
- lora_scale
- LoRA additive scale.
- num_outputs
- Number of images to output.
- refine_steps
- for base_image_refiner, the number of steps to refine, defaults to num_inference_steps
- guidance_scale
- Scale for classifier-free guidance
- apply_watermark
- Applies a watermark to enable determining if an image is generated in downstream applications. If you have other provisions for generating or deploying images safely, you can use this to disable watermarking.
- high_noise_frac
- for expert_ensemble_refiner, the fraction of noise to use
- negative_prompt
- Input Negative Prompt
- prompt_strength
- Prompt strength when using img2img / inpaint. 1.0 corresponds to full destruction of information in image
- num_inference_steps
- Number of denoising steps
Output Schema
Output
Example Execution Logs
Using seed: 38525 Prompt: A futuristic close-up portrait photo in the style of TRN txt2img mode 0%| | 0/45 [00:00<?, ?it/s] 2%|▏ | 1/45 [00:00<00:11, 3.70it/s] 4%|▍ | 2/45 [00:00<00:11, 3.70it/s] 7%|▋ | 3/45 [00:00<00:11, 3.70it/s] 9%|▉ | 4/45 [00:01<00:11, 3.68it/s] 11%|█ | 5/45 [00:01<00:10, 3.69it/s] 13%|█▎ | 6/45 [00:01<00:10, 3.69it/s] 16%|█▌ | 7/45 [00:01<00:10, 3.69it/s] 18%|█▊ | 8/45 [00:02<00:10, 3.68it/s] 20%|██ | 9/45 [00:02<00:09, 3.68it/s] 22%|██▏ | 10/45 [00:02<00:09, 3.68it/s] 24%|██▍ | 11/45 [00:02<00:09, 3.68it/s] 27%|██▋ | 12/45 [00:03<00:08, 3.67it/s] 29%|██▉ | 13/45 [00:03<00:08, 3.67it/s] 31%|███ | 14/45 [00:03<00:08, 3.67it/s] 33%|███▎ | 15/45 [00:04<00:08, 3.67it/s] 36%|███▌ | 16/45 [00:04<00:07, 3.67it/s] 38%|███▊ | 17/45 [00:04<00:07, 3.67it/s] 40%|████ | 18/45 [00:04<00:07, 3.67it/s] 42%|████▏ | 19/45 [00:05<00:07, 3.67it/s] 44%|████▍ | 20/45 [00:05<00:06, 3.67it/s] 47%|████▋ | 21/45 [00:05<00:06, 3.67it/s] 49%|████▉ | 22/45 [00:05<00:06, 3.67it/s] 51%|█████ | 23/45 [00:06<00:05, 3.67it/s] 53%|█████▎ | 24/45 [00:06<00:05, 3.67it/s] 56%|█████▌ | 25/45 [00:06<00:05, 3.67it/s] 58%|█████▊ | 26/45 [00:07<00:05, 3.67it/s] 60%|██████ | 27/45 [00:07<00:04, 3.67it/s] 62%|██████▏ | 28/45 [00:07<00:04, 3.67it/s] 64%|██████▍ | 29/45 [00:07<00:04, 3.66it/s] 67%|██████▋ | 30/45 [00:08<00:04, 3.67it/s] 69%|██████▉ | 31/45 [00:08<00:03, 3.66it/s] 71%|███████ | 32/45 [00:08<00:03, 3.66it/s] 73%|███████▎ | 33/45 [00:08<00:03, 3.66it/s] 76%|███████▌ | 34/45 [00:09<00:03, 3.66it/s] 78%|███████▊ | 35/45 [00:09<00:02, 3.66it/s] 80%|████████ | 36/45 [00:09<00:02, 3.66it/s] 82%|████████▏ | 37/45 [00:10<00:02, 3.66it/s] 84%|████████▍ | 38/45 [00:10<00:01, 3.66it/s] 87%|████████▋ | 39/45 [00:10<00:01, 3.66it/s] 89%|████████▉ | 40/45 [00:10<00:01, 3.66it/s] 91%|█████████ | 41/45 [00:11<00:01, 3.66it/s] 93%|█████████▎| 42/45 [00:11<00:00, 3.66it/s] 96%|█████████▌| 43/45 [00:11<00:00, 3.66it/s] 98%|█████████▊| 44/45 [00:11<00:00, 3.66it/s] 100%|██████████| 45/45 [00:12<00:00, 3.66it/s] 100%|██████████| 45/45 [00:12<00:00, 3.67it/s] 0%| | 0/5 [00:00<?, ?it/s] 20%|██ | 1/5 [00:00<00:00, 4.33it/s] 40%|████ | 2/5 [00:00<00:00, 4.31it/s] 60%|██████ | 3/5 [00:00<00:00, 4.30it/s] 80%|████████ | 4/5 [00:00<00:00, 4.29it/s] 100%|██████████| 5/5 [00:01<00:00, 4.28it/s] 100%|██████████| 5/5 [00:01<00:00, 4.29it/s]
Version Details
- Version ID
fd920825e12db2a942f8a9cac40ad4f624a34a06faba3ac1b44a5305df8c6e2d- Version Created
- August 8, 2023