spider333/dadka 🖼️🔢❓📝✓ → 🖼️
About

Example Output
Prompt:
"artsy picture of ginger HOTCHIC with big boobs holding painting brush, wearing painting suite, being dirty from colors, with pink, camp splashy background , vivid colours High definition "
Output




Performance Metrics
35.48s
Prediction Time
44.42s
Total Time
All Input Parameters
{ "model": "dev", "prompt": "artsy picture of ginger HOTCHIC with big boobs holding painting brush, wearing painting suite, being dirty from colors, with pink, camp splashy background , vivid colours High definition ", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 4, "aspect_ratio": "4:5", "output_format": "png", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 32 }
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
2025-01-29 07:46:51.070 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-29 07:46:51.071 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 95%|█████████▍| 288/304 [00:00<00:00, 2876.84it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2793.43it/s] 2025-01-29 07:46:51.180 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s free=29055690444800 Downloading weights 2025-01-29T07:46:51Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpyvnf27q9/weights url=https://replicate.delivery/xezq/kzhfD4NVecvxGkEfZNqfYfO22j9pQvh2tnIB3K61tfIysHeEKA/trained_model.tar 2025-01-29T07:46:57Z | INFO | [ Complete ] dest=/tmp/tmpyvnf27q9/weights size="258 MB" total_elapsed=6.498s url=https://replicate.delivery/xezq/kzhfD4NVecvxGkEfZNqfYfO22j9pQvh2tnIB3K61tfIysHeEKA/trained_model.tar Downloaded weights in 6.52s 2025-01-29 07:46:57.706 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/22c481f1bc1d7f9a 2025-01-29 07:46:57.791 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2025-01-29 07:46:57.791 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-29 07:46:57.792 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 95%|█████████▍| 288/304 [00:00<00:00, 2868.08it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2785.36it/s] 2025-01-29 07:46:57.901 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.19s Using seed: 14940 0it [00:00, ?it/s] 1it [00:00, 9.16it/s] 2it [00:00, 6.43it/s] 3it [00:00, 5.86it/s] 4it [00:00, 5.63it/s] 5it [00:00, 5.48it/s] 6it [00:01, 5.34it/s] 7it [00:01, 5.29it/s] 8it [00:01, 5.29it/s] 9it [00:01, 5.29it/s] 10it [00:01, 5.29it/s] 11it [00:02, 5.29it/s] 12it [00:02, 5.29it/s] 13it [00:02, 5.28it/s] 14it [00:02, 5.29it/s] 15it [00:02, 5.29it/s] 16it [00:02, 5.27it/s] 17it [00:03, 5.26it/s] 18it [00:03, 5.24it/s] 19it [00:03, 5.26it/s] 20it [00:03, 5.25it/s] 21it [00:03, 5.26it/s] 22it [00:04, 5.27it/s] 23it [00:04, 5.24it/s] 24it [00:04, 5.25it/s] 25it [00:04, 5.25it/s] 26it [00:04, 5.24it/s] 27it [00:05, 5.23it/s] 28it [00:05, 5.22it/s] 29it [00:05, 5.22it/s] 30it [00:05, 5.24it/s] 31it [00:05, 5.26it/s] 32it [00:06, 5.27it/s] 32it [00:06, 5.33it/s] 0it [00:00, ?it/s] 1it [00:00, 5.31it/s] 2it [00:00, 5.24it/s] 3it [00:00, 5.26it/s] 4it [00:00, 5.25it/s] 5it [00:00, 5.22it/s] 6it [00:01, 5.22it/s] 7it [00:01, 5.22it/s] 8it [00:01, 5.21it/s] 9it [00:01, 5.23it/s] 10it [00:01, 5.22it/s] 11it [00:02, 5.23it/s] 12it [00:02, 5.23it/s] 13it [00:02, 5.24it/s] 14it [00:02, 5.23it/s] 15it [00:02, 5.23it/s] 16it [00:03, 5.24it/s] 17it [00:03, 5.22it/s] 18it [00:03, 5.24it/s] 19it [00:03, 5.23it/s] 20it [00:03, 5.23it/s] 21it [00:04, 5.24it/s] 22it [00:04, 5.22it/s] 23it [00:04, 5.19it/s] 24it [00:04, 5.21it/s] 25it [00:04, 5.23it/s] 26it [00:04, 5.25it/s] 27it [00:05, 5.26it/s] 28it [00:05, 5.23it/s] 29it [00:05, 5.21it/s] 30it [00:05, 5.23it/s] 31it [00:05, 5.24it/s] 32it [00:06, 5.25it/s] 32it [00:06, 5.23it/s] 0it [00:00, ?it/s] 1it [00:00, 5.21it/s] 2it [00:00, 5.18it/s] 3it [00:00, 5.22it/s] 4it [00:00, 5.23it/s] 5it [00:00, 5.24it/s] 6it [00:01, 5.22it/s] 7it [00:01, 5.20it/s] 8it [00:01, 5.19it/s] 9it [00:01, 5.20it/s] 10it [00:01, 5.22it/s] 11it [00:02, 5.22it/s] 12it [00:02, 5.24it/s] 13it [00:02, 5.24it/s] 14it [00:02, 5.23it/s] 15it [00:02, 5.23it/s] 16it [00:03, 5.23it/s] 17it [00:03, 5.20it/s] 18it [00:03, 5.23it/s] 19it [00:03, 5.21it/s] 20it [00:03, 5.23it/s] 21it [00:04, 5.22it/s] 22it [00:04, 5.22it/s] 23it [00:04, 5.21it/s] 24it [00:04, 5.20it/s] 25it [00:04, 5.20it/s] 26it [00:04, 5.23it/s] 27it [00:05, 5.24it/s] 28it [00:05, 5.24it/s] 29it [00:05, 5.22it/s] 30it [00:05, 5.20it/s] 31it [00:05, 5.20it/s] 32it [00:06, 5.20it/s] 32it [00:06, 5.22it/s] 0it [00:00, ?it/s] 1it [00:00, 5.29it/s] 2it [00:00, 5.24it/s] 3it [00:00, 5.26it/s] 4it [00:00, 5.26it/s] 5it [00:00, 5.23it/s] 6it [00:01, 5.21it/s] 7it [00:01, 5.21it/s] 8it [00:01, 5.19it/s] 9it [00:01, 5.19it/s] 10it [00:01, 5.19it/s] 11it [00:02, 5.21it/s] 12it [00:02, 5.23it/s] 13it [00:02, 5.24it/s] 14it [00:02, 5.22it/s] 15it [00:02, 5.22it/s] 16it [00:03, 5.23it/s] 17it [00:03, 5.24it/s] 18it [00:03, 5.22it/s] 19it [00:03, 5.19it/s] 20it [00:03, 5.21it/s] 21it [00:04, 5.20it/s] 22it [00:04, 5.20it/s] 23it [00:04, 5.19it/s] 24it [00:04, 5.20it/s] 25it [00:04, 5.21it/s] 26it [00:04, 5.23it/s] 27it [00:05, 5.24it/s] 28it [00:05, 5.24it/s] 29it [00:05, 5.21it/s] 30it [00:05, 5.20it/s] 31it [00:05, 5.18it/s] 32it [00:06, 5.18it/s] 32it [00:06, 5.21it/s] Total safe images: 4 out of 4
Version Details
- Version ID
868ac956b21fe199e6ffa515bdbc12f7493c0bb6ee78d6ebb3c1f53f9970ab86
- Version Created
- January 29, 2025