shapestudio/owesa 🖼️🔢❓📝✓ → 🖼️
About
Example Output
Prompt:
"black-and-white line drawing of a face in a cartoon style. The illustration of animal. The lines are smooth and minimal, giving it a clean and modern look, almost like an icon or avatar. The expression is cheerful and friendly. in the style of TOK "
Output



Performance Metrics
12.55s
Prediction Time
12.58s
Total Time
All Input Parameters
{
"model": "schnell",
"prompt": "black-and-white line drawing of a face in a cartoon style. The illustration of animal. The lines are smooth and minimal, giving it a clean and modern look, almost like an icon or avatar. The expression is cheerful and friendly. in the style of TOK ",
"go_fast": true,
"lora_scale": 0.86,
"megapixels": "1",
"num_outputs": 4,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 3,
"output_quality": 80,
"prompt_strength": 0.8,
"extra_lora_scale": 1,
"num_inference_steps": 28
}
Input Parameters
- mask
- Image mask for image inpainting mode. If provided, aspect_ratio, width, and height inputs are ignored.
- seed
- Random seed. Set for reproducible generation
- image
- Input image for image to image or inpainting mode. If provided, aspect_ratio, width, and height inputs are ignored.
- model
- Which model to run inference with. The dev model performs best with around 28 inference steps but the schnell model only needs 4 steps.
- width
- Width of generated image. Only works if `aspect_ratio` is set to custom. Will be rounded to nearest multiple of 16. Incompatible with fast generation
- height
- Height of generated image. Only works if `aspect_ratio` is set to custom. Will be rounded to nearest multiple of 16. Incompatible with fast generation
- prompt (required)
- Prompt for generated image. If you include the `trigger_word` used in the training process you are more likely to activate the trained object, style, or concept in the resulting image.
- go_fast
- Run faster predictions with model optimized for speed (currently fp8 quantized); disable to run in original bf16
- extra_lora
- Load LoRA weights. Supports Replicate models in the format <owner>/<username> or <owner>/<username>/<version>, HuggingFace URLs in the format huggingface.co/<owner>/<model-name>, CivitAI URLs in the format civitai.com/models/<id>[/<model-name>], or arbitrary .safetensors URLs from the Internet. For example, 'fofr/flux-pixar-cars'
- lora_scale
- Determines how strongly the main LoRA should be applied. Sane results between 0 and 1 for base inference. For go_fast we apply a 1.5x multiplier to this value; we've generally seen good performance when scaling the base value by that amount. You may still need to experiment to find the best value for your particular lora.
- megapixels
- Approximate number of megapixels for generated image
- num_outputs
- Number of outputs to generate
- aspect_ratio
- Aspect ratio for the generated image. If custom is selected, uses height and width below & will run in bf16 mode
- output_format
- Format of the output images
- guidance_scale
- Guidance scale for the diffusion process. Lower values can give more realistic images. Good values to try are 2, 2.5, 3 and 3.5
- output_quality
- Quality when saving the output images, from 0 to 100. 100 is best quality, 0 is lowest quality. Not relevant for .png outputs
- prompt_strength
- Prompt strength when using img2img. 1.0 corresponds to full destruction of information in image
- extra_lora_scale
- Determines how strongly the extra LoRA should be applied. Sane results between 0 and 1 for base inference. For go_fast we apply a 1.5x multiplier to this value; we've generally seen good performance when scaling the base value by that amount. You may still need to experiment to find the best value for your particular lora.
- replicate_weights
- Load LoRA weights. Supports Replicate models in the format <owner>/<username> or <owner>/<username>/<version>, HuggingFace URLs in the format huggingface.co/<owner>/<model-name>, CivitAI URLs in the format civitai.com/models/<id>[/<model-name>], or arbitrary .safetensors URLs from the Internet. For example, 'fofr/flux-pixar-cars'
- num_inference_steps
- Number of denoising steps. More steps can give more detailed images, but take longer.
- disable_safety_checker
- Disable safety checker for generated images.
Output Schema
Output
Example Execution Logs
2025-10-01 13:40:06.431 | INFO | fp8.lora_loading:convert_lora_weights:502 - Loading LoRA weights for /src/weights-cache/6f6a71c8ef84462e 2025-10-01 13:40:06.507 | INFO | fp8.lora_loading:convert_lora_weights:523 - LoRA weights loaded 2025-10-01 13:40:06.507 | DEBUG | fp8.lora_loading:apply_lora_to_model_and_optionally_store_clones:610 - Extracting keys 2025-10-01 13:40:06.507 | DEBUG | fp8.lora_loading:apply_lora_to_model_and_optionally_store_clones:617 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 44%|████▍ | 135/304 [00:00<00:00, 1343.86it/s] Applying LoRA: 89%|████████▉ | 270/304 [00:00<00:00, 1086.00it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 1081.99it/s] 2025-10-01 13:40:06.788 | INFO | fp8.lora_loading:apply_lora_to_model_and_optionally_store_clones:669 - Loading LoRA in fp8 2025-10-01 13:40:06.788 | SUCCESS | fp8.lora_loading:load_lora:547 - LoRA applied in 0.36s running quantized prediction Using seed: 3335393908 0%| | 0/28 [00:00<?, ?it/s] 11%|█ | 3/28 [00:00<00:01, 16.00it/s] 18%|█▊ | 5/28 [00:00<00:01, 13.18it/s] 25%|██▌ | 7/28 [00:00<00:01, 12.25it/s] 32%|███▏ | 9/28 [00:00<00:01, 11.81it/s] 39%|███▉ | 11/28 [00:00<00:01, 11.37it/s] 46%|████▋ | 13/28 [00:01<00:01, 11.18it/s] 54%|█████▎ | 15/28 [00:01<00:01, 11.14it/s] 61%|██████ | 17/28 [00:01<00:00, 11.13it/s] 68%|██████▊ | 19/28 [00:01<00:00, 11.14it/s] 75%|███████▌ | 21/28 [00:01<00:00, 11.09it/s] 82%|████████▏ | 23/28 [00:02<00:00, 10.98it/s] 89%|████████▉ | 25/28 [00:02<00:00, 10.99it/s] 96%|█████████▋| 27/28 [00:02<00:00, 11.01it/s] 100%|██████████| 28/28 [00:02<00:00, 11.38it/s] 0%| | 0/28 [00:00<?, ?it/s] 7%|▋ | 2/28 [00:00<00:02, 11.16it/s] 14%|█▍ | 4/28 [00:00<00:02, 10.97it/s] 21%|██▏ | 6/28 [00:00<00:02, 10.91it/s] 29%|██▊ | 8/28 [00:00<00:01, 10.91it/s] 36%|███▌ | 10/28 [00:00<00:01, 10.95it/s] 43%|████▎ | 12/28 [00:01<00:01, 10.98it/s] 50%|█████ | 14/28 [00:01<00:01, 10.98it/s] 57%|█████▋ | 16/28 [00:01<00:01, 10.92it/s] 64%|██████▍ | 18/28 [00:01<00:00, 10.93it/s] 71%|███████▏ | 20/28 [00:01<00:00, 10.95it/s] 79%|███████▊ | 22/28 [00:02<00:00, 10.97it/s] 86%|████████▌ | 24/28 [00:02<00:00, 10.99it/s] 93%|█████████▎| 26/28 [00:02<00:00, 10.96it/s] 100%|██████████| 28/28 [00:02<00:00, 10.95it/s] 100%|██████████| 28/28 [00:02<00:00, 10.95it/s] 0%| | 0/28 [00:00<?, ?it/s] 7%|▋ | 2/28 [00:00<00:02, 10.99it/s] 14%|█▍ | 4/28 [00:00<00:02, 10.97it/s] 21%|██▏ | 6/28 [00:00<00:02, 10.99it/s] 29%|██▊ | 8/28 [00:00<00:01, 10.99it/s] 36%|███▌ | 10/28 [00:00<00:01, 10.93it/s] 43%|████▎ | 12/28 [00:01<00:01, 10.92it/s] 50%|█████ | 14/28 [00:01<00:01, 10.95it/s] 57%|█████▋ | 16/28 [00:01<00:01, 10.97it/s] 64%|██████▍ | 18/28 [00:01<00:00, 10.97it/s] 71%|███████▏ | 20/28 [00:01<00:00, 10.97it/s] 79%|███████▊ | 22/28 [00:02<00:00, 10.94it/s] 86%|████████▌ | 24/28 [00:02<00:00, 10.94it/s] 93%|█████████▎| 26/28 [00:02<00:00, 10.95it/s] 100%|██████████| 28/28 [00:02<00:00, 10.96it/s] 100%|██████████| 28/28 [00:02<00:00, 10.96it/s] 0%| | 0/28 [00:00<?, ?it/s] 7%|▋ | 2/28 [00:00<00:02, 10.95it/s] 14%|█▍ | 4/28 [00:00<00:02, 10.93it/s] 21%|██▏ | 6/28 [00:00<00:02, 10.93it/s] 29%|██▊ | 8/28 [00:00<00:01, 10.95it/s] 36%|███▌ | 10/28 [00:00<00:01, 10.95it/s] 43%|████▎ | 12/28 [00:01<00:01, 10.95it/s] 50%|█████ | 14/28 [00:01<00:01, 10.96it/s] 57%|█████▋ | 16/28 [00:01<00:01, 10.96it/s] 64%|██████▍ | 18/28 [00:01<00:00, 10.95it/s] 71%|███████▏ | 20/28 [00:01<00:00, 10.94it/s] 79%|███████▊ | 22/28 [00:02<00:00, 10.94it/s] 86%|████████▌ | 24/28 [00:02<00:00, 10.94it/s] 93%|█████████▎| 26/28 [00:02<00:00, 10.93it/s] 100%|██████████| 28/28 [00:02<00:00, 10.96it/s] 100%|██████████| 28/28 [00:02<00:00, 10.95it/s] Total safe images: 4 out of 4
Version Details
- Version ID
4ef7cc4fb742cacb90b8e2eec5baec753a7758d7a88a0dbb93cb9595712a280c- Version Created
- September 24, 2025