justmalhar/sxdl-sketchnotes 🖼️🔢📝❓✓ → 🖼️
About
SDXL Fine tuned on sketchnote style images. Prompt Prefix: a sketchnote photo of TOK
Example Output
Prompt:
"a sketchnote photo of TOK explaining types of sorting algorithms"
Output



Performance Metrics
53.31s
Prediction Time
58.64s
Total Time
All Input Parameters
{
"width": 1024,
"height": 1024,
"prompt": "a sketchnote photo of TOK explaining types of sorting algorithms",
"refine": "expert_ensemble_refiner",
"scheduler": "K_EULER",
"lora_scale": 0.6,
"num_outputs": 4,
"guidance_scale": 7.5,
"apply_watermark": false,
"high_noise_frac": 0.8,
"negative_prompt": "",
"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. 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](https://replicate.com/docs/how-does-replicate-work#safety)
Output Schema
Output
Example Execution Logs
Using seed: 9272 Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: a sketchnote photo of <s0><s1> explaining types of sorting algorithms txt2img mode 0%| | 0/40 [00:00<?, ?it/s] 2%|▎ | 1/40 [00:00<00:35, 1.09it/s] 5%|▌ | 2/40 [00:01<00:34, 1.09it/s] 8%|▊ | 3/40 [00:02<00:34, 1.09it/s] 10%|█ | 4/40 [00:03<00:33, 1.09it/s] 12%|█▎ | 5/40 [00:04<00:32, 1.09it/s] 15%|█▌ | 6/40 [00:05<00:31, 1.08it/s] 18%|█▊ | 7/40 [00:06<00:30, 1.08it/s] 20%|██ | 8/40 [00:07<00:29, 1.08it/s] 22%|██▎ | 9/40 [00:08<00:28, 1.08it/s] 25%|██▌ | 10/40 [00:09<00:27, 1.08it/s] 28%|██▊ | 11/40 [00:10<00:26, 1.08it/s] 30%|███ | 12/40 [00:11<00:25, 1.08it/s] 32%|███▎ | 13/40 [00:11<00:24, 1.08it/s] 35%|███▌ | 14/40 [00:12<00:24, 1.08it/s] 38%|███▊ | 15/40 [00:13<00:23, 1.08it/s] 40%|████ | 16/40 [00:14<00:22, 1.08it/s] 42%|████▎ | 17/40 [00:15<00:21, 1.08it/s] 45%|████▌ | 18/40 [00:16<00:20, 1.08it/s] 48%|████▊ | 19/40 [00:17<00:19, 1.08it/s] 50%|█████ | 20/40 [00:18<00:18, 1.08it/s] 52%|█████▎ | 21/40 [00:19<00:17, 1.08it/s] 55%|█████▌ | 22/40 [00:20<00:16, 1.08it/s] 57%|█████▊ | 23/40 [00:21<00:15, 1.08it/s] 60%|██████ | 24/40 [00:22<00:14, 1.08it/s] 62%|██████▎ | 25/40 [00:23<00:13, 1.08it/s] 65%|██████▌ | 26/40 [00:24<00:12, 1.08it/s] 68%|██████▊ | 27/40 [00:24<00:12, 1.08it/s] 70%|███████ | 28/40 [00:25<00:11, 1.08it/s] 72%|███████▎ | 29/40 [00:26<00:10, 1.08it/s] 75%|███████▌ | 30/40 [00:27<00:09, 1.08it/s] 78%|███████▊ | 31/40 [00:28<00:08, 1.08it/s] 80%|████████ | 32/40 [00:29<00:07, 1.08it/s] 82%|████████▎ | 33/40 [00:30<00:06, 1.08it/s] 85%|████████▌ | 34/40 [00:31<00:05, 1.08it/s] 88%|████████▊ | 35/40 [00:32<00:04, 1.08it/s] 90%|█████████ | 36/40 [00:33<00:03, 1.08it/s] 92%|█████████▎| 37/40 [00:34<00:02, 1.08it/s] 95%|█████████▌| 38/40 [00:35<00:01, 1.08it/s] 98%|█████████▊| 39/40 [00:36<00:00, 1.08it/s] 100%|██████████| 40/40 [00:36<00:00, 1.08it/s] 100%|██████████| 40/40 [00:36<00:00, 1.08it/s] 0%| | 0/10 [00:00<?, ?it/s] 10%|█ | 1/10 [00:00<00:08, 1.08it/s] 20%|██ | 2/10 [00:01<00:07, 1.08it/s] 30%|███ | 3/10 [00:02<00:06, 1.09it/s] 40%|████ | 4/10 [00:03<00:05, 1.08it/s] 50%|█████ | 5/10 [00:04<00:04, 1.08it/s] 60%|██████ | 6/10 [00:05<00:03, 1.08it/s] 70%|███████ | 7/10 [00:06<00:02, 1.08it/s] 80%|████████ | 8/10 [00:07<00:01, 1.08it/s] 90%|█████████ | 9/10 [00:08<00:00, 1.08it/s] 100%|██████████| 10/10 [00:09<00:00, 1.08it/s] 100%|██████████| 10/10 [00:09<00:00, 1.08it/s]
Version Details
- Version ID
988b3a09e1c2441fb4f22a04aeae435ddb0467357b7dec3337fef7ccc6f7df7c- Version Created
- May 22, 2024