profdl/logos 🖼️🔢📝❓✓ → 🖼️
About
Trained on logo designs, black logos on white backgrounds
Example Output
Prompt:
"iconic logo in the style of logo"
Output
Performance Metrics
9.19s
Prediction Time
12.24s
Total Time
All Input Parameters
{
"width": 1024,
"height": 1024,
"prompt": "iconic logo in the style of logo",
"refine": "no_refiner",
"scheduler": "K_EULER_ANCESTRAL",
"lora_scale": 1,
"num_outputs": 1,
"guidance_scale": 7.5,
"apply_watermark": true,
"high_noise_frac": 0.8,
"negative_prompt": "cropped, lines, linear, off center, circles, curves, color, texture, light, shading, complex, maximal, too much detail, ",
"prompt_strength": 0.9,
"num_inference_steps": 27
}
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. Only applicable on trained models.
- 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
- replicate_weights
- Replicate LoRA weights to use. Leave blank to use the default weights.
- num_inference_steps
- Number of denoising steps
- disable_safety_checker
- Disable safety checker for generated images. This feature is only available through the API. See https://replicate.com/docs/how-does-replicate-work#safety
Output Schema
Output
Example Execution Logs
Using seed: 26276 Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: iconic logo in the style of logo txt2img mode 0%| | 0/27 [00:00<?, ?it/s] 4%|▎ | 1/27 [00:00<00:07, 3.66it/s] 7%|▋ | 2/27 [00:00<00:06, 3.66it/s] 11%|█ | 3/27 [00:00<00:06, 3.67it/s] 15%|█▍ | 4/27 [00:01<00:06, 3.66it/s] 19%|█▊ | 5/27 [00:01<00:06, 3.66it/s] 22%|██▏ | 6/27 [00:01<00:05, 3.66it/s] 26%|██▌ | 7/27 [00:01<00:05, 3.66it/s] 30%|██▉ | 8/27 [00:02<00:05, 3.66it/s] 33%|███▎ | 9/27 [00:02<00:04, 3.66it/s] 37%|███▋ | 10/27 [00:02<00:04, 3.66it/s] 41%|████ | 11/27 [00:03<00:04, 3.65it/s] 44%|████▍ | 12/27 [00:03<00:04, 3.65it/s] 48%|████▊ | 13/27 [00:03<00:03, 3.65it/s] 52%|█████▏ | 14/27 [00:03<00:03, 3.65it/s] 56%|█████▌ | 15/27 [00:04<00:03, 3.65it/s] 59%|█████▉ | 16/27 [00:04<00:03, 3.65it/s] 63%|██████▎ | 17/27 [00:04<00:02, 3.65it/s] 67%|██████▋ | 18/27 [00:04<00:02, 3.65it/s] 70%|███████ | 19/27 [00:05<00:02, 3.65it/s] 74%|███████▍ | 20/27 [00:05<00:01, 3.65it/s] 78%|███████▊ | 21/27 [00:05<00:01, 3.65it/s] 81%|████████▏ | 22/27 [00:06<00:01, 3.65it/s] 85%|████████▌ | 23/27 [00:06<00:01, 3.65it/s] 89%|████████▉ | 24/27 [00:06<00:00, 3.65it/s] 93%|█████████▎| 25/27 [00:06<00:00, 3.65it/s] 96%|█████████▋| 26/27 [00:07<00:00, 3.65it/s] 100%|██████████| 27/27 [00:07<00:00, 3.65it/s] 100%|██████████| 27/27 [00:07<00:00, 3.65it/s]
Version Details
- Version ID
3dc046194d013cb37ad388eb72f2dd4dff2dcde318b5317d342367f802843595- Version Created
- December 12, 2023