stonerjay420/scene-hair 🖼️🔢❓📝✓ → 🖼️
About
Example Output
Prompt:
"SceneKid, petite, ashen-skinned, innocent, 18yo, 1girl, short crop top, daisy dukes, blue eyes, flawless skin, high definition"
Output

Performance Metrics
15.34s
Prediction Time
15.45s
Total Time
All Input Parameters
{
"model": "dev",
"width": 727,
"height": 1374,
"prompt": "SceneKid, petite, ashen-skinned, innocent, 18yo, 1girl, short crop top, daisy dukes, blue eyes, flawless skin, high definition",
"go_fast": true,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 4,
"aspect_ratio": "9:16",
"output_format": "png",
"guidance_scale": 2.21,
"output_quality": 100,
"prompt_strength": 0.8,
"extra_lora_scale": 1,
"num_inference_steps": 33
}
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
Lora https://replicate.delivery/yhqm/PezhfyyEv2nAXkCRPB0Tp9JDtCyHjyFRspQOes3vVVl1gufNB/trained_model.tar already loaded running quantized prediction Using seed: 895564276 0%| | 0/33 [00:00<?, ?it/s] 9%|▉ | 3/33 [00:00<00:01, 15.70it/s] 15%|█▌ | 5/33 [00:00<00:02, 12.79it/s] 21%|██ | 7/33 [00:00<00:02, 11.77it/s] 27%|██▋ | 9/33 [00:00<00:02, 11.33it/s] 33%|███▎ | 11/33 [00:00<00:02, 10.76it/s] 39%|███▉ | 13/33 [00:01<00:01, 10.61it/s] 45%|████▌ | 15/33 [00:01<00:01, 10.57it/s] 52%|█████▏ | 17/33 [00:01<00:01, 10.58it/s] 58%|█████▊ | 19/33 [00:01<00:01, 10.55it/s] 64%|██████▎ | 21/33 [00:01<00:01, 10.44it/s] 70%|██████▉ | 23/33 [00:02<00:00, 10.37it/s] 76%|███████▌ | 25/33 [00:02<00:00, 10.43it/s] 82%|████████▏ | 27/33 [00:02<00:00, 10.47it/s] 88%|████████▊ | 29/33 [00:02<00:00, 10.52it/s] 94%|█████████▍| 31/33 [00:02<00:00, 10.47it/s] 100%|██████████| 33/33 [00:03<00:00, 10.41it/s] 100%|██████████| 33/33 [00:03<00:00, 10.75it/s] 0%| | 0/33 [00:00<?, ?it/s] 6%|▌ | 2/33 [00:00<00:02, 10.46it/s] 12%|█▏ | 4/33 [00:00<00:02, 10.46it/s] 18%|█▊ | 6/33 [00:00<00:02, 10.47it/s] 24%|██▍ | 8/33 [00:00<00:02, 10.40it/s] 30%|███ | 10/33 [00:00<00:02, 10.37it/s] 36%|███▋ | 12/33 [00:01<00:02, 10.37it/s] 42%|████▏ | 14/33 [00:01<00:01, 10.39it/s] 48%|████▊ | 16/33 [00:01<00:01, 10.43it/s] 55%|█████▍ | 18/33 [00:01<00:01, 10.42it/s] 61%|██████ | 20/33 [00:01<00:01, 10.41it/s] 67%|██████▋ | 22/33 [00:02<00:01, 10.39it/s] 73%|███████▎ | 24/33 [00:02<00:00, 10.43it/s] 79%|███████▉ | 26/33 [00:02<00:00, 10.44it/s] 85%|████████▍ | 28/33 [00:02<00:00, 10.41it/s] 91%|█████████ | 30/33 [00:02<00:00, 10.40it/s] 97%|█████████▋| 32/33 [00:03<00:00, 10.37it/s] 100%|██████████| 33/33 [00:03<00:00, 10.40it/s] 0%| | 0/33 [00:00<?, ?it/s] 6%|▌ | 2/33 [00:00<00:02, 10.59it/s] 12%|█▏ | 4/33 [00:00<00:02, 10.51it/s] 18%|█▊ | 6/33 [00:00<00:02, 10.50it/s] 24%|██▍ | 8/33 [00:00<00:02, 10.47it/s] 30%|███ | 10/33 [00:00<00:02, 10.44it/s] 36%|███▋ | 12/33 [00:01<00:02, 10.41it/s] 42%|████▏ | 14/33 [00:01<00:01, 10.44it/s] 48%|████▊ | 16/33 [00:01<00:01, 10.44it/s] 55%|█████▍ | 18/33 [00:01<00:01, 10.42it/s] 61%|██████ | 20/33 [00:01<00:01, 10.40it/s] 67%|██████▋ | 22/33 [00:02<00:01, 10.40it/s] 73%|███████▎ | 24/33 [00:02<00:00, 10.39it/s] 79%|███████▉ | 26/33 [00:02<00:00, 10.40it/s] 85%|████████▍ | 28/33 [00:02<00:00, 10.38it/s] 91%|█████████ | 30/33 [00:02<00:00, 10.35it/s] 97%|█████████▋| 32/33 [00:03<00:00, 10.37it/s] 100%|██████████| 33/33 [00:03<00:00, 10.41it/s] 0%| | 0/33 [00:00<?, ?it/s] 6%|▌ | 2/33 [00:00<00:02, 10.44it/s] 12%|█▏ | 4/33 [00:00<00:02, 10.41it/s] 18%|█▊ | 6/33 [00:00<00:02, 10.35it/s] 24%|██▍ | 8/33 [00:00<00:02, 10.34it/s] 30%|███ | 10/33 [00:00<00:02, 10.32it/s] 36%|███▋ | 12/33 [00:01<00:02, 10.37it/s] 42%|████▏ | 14/33 [00:01<00:01, 10.40it/s] 48%|████▊ | 16/33 [00:01<00:01, 10.39it/s] 55%|█████▍ | 18/33 [00:01<00:01, 10.44it/s] 61%|██████ | 20/33 [00:01<00:01, 10.42it/s] 67%|██████▋ | 22/33 [00:02<00:01, 10.42it/s] 73%|███████▎ | 24/33 [00:02<00:00, 10.40it/s] 79%|███████▉ | 26/33 [00:02<00:00, 10.38it/s] 85%|████████▍ | 28/33 [00:02<00:00, 10.36it/s] 91%|█████████ | 30/33 [00:02<00:00, 10.42it/s] 97%|█████████▋| 32/33 [00:03<00:00, 10.44it/s] 100%|██████████| 33/33 [00:03<00:00, 10.40it/s] NSFW content detected in image 1 NSFW content detected in image 3 Total safe images: 2 out of 4
Version Details
- Version ID
8de8d7803b4a520bc590fa37dc19fc7a47b80806746d053b909df3729faf19b6- Version Created
- September 23, 2024