juliusk24/jakob 🖼️🔢❓📝✓ → 🖼️
About
Example Output
Prompt:
"The camera captures the man in a close-up shot, focusing primarily on his upper body and face, revealing intricate details of his sharp, dark pinstripe suit and subtly patterned tie. His crisp white shirt peeks perfectly under the lapels, and a neatly folded pocket square adds a touch of refinement. The close framing emphasizes his composed expression, well-groomed hair, and confident gaze. The fine textures of the suit fabric are visible, illuminated by soft natural light from nearby windows. In the blurred background, hints of greenery and modern architecture subtly set the scene."
Output
Performance Metrics
28.45s
Prediction Time
28.46s
Total Time
All Input Parameters
{
"image": "https://replicate.delivery/pbxt/Lt8KPYG1BIeIvxFryYBExEDPpqdafLvZcIfxqcKHVDV9GQK7/3f646442-8e3d-4db3-bcc4-a7d9461528da.png",
"model": "dev",
"prompt": "The camera captures the man in a close-up shot, focusing primarily on his upper body and face, revealing intricate details of his sharp, dark pinstripe suit and subtly patterned tie. His crisp white shirt peeks perfectly under the lapels, and a neatly folded pocket square adds a touch of refinement. The close framing emphasizes his composed expression, well-groomed hair, and confident gaze. The fine textures of the suit fabric are visible, illuminated by soft natural light from nearby windows. In the blurred background, hints of greenery and modern architecture subtly set the scene.",
"lora_scale": 1,
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "png",
"guidance_scale": 2.5,
"output_quality": 90,
"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
Using seed: 38756 Prompt: The camera captures the man in a close-up shot, focusing primarily on his upper body and face, revealing intricate details of his sharp, dark pinstripe suit and subtly patterned tie. His crisp white shirt peeks perfectly under the lapels, and a neatly folded pocket square adds a touch of refinement. The close framing emphasizes his composed expression, well-groomed hair, and confident gaze. The fine textures of the suit fabric are visible, illuminated by soft natural light from nearby windows. In the blurred background, hints of greenery and modern architecture subtly set the scene. [!] Resizing input image from 1534x2048 to 1536x2048 [!] img2img mode [!] Using dev model for img2img Using dev model Loaded LoRAs in 0.70s 0%| | 0/23 [00:00<?, ?it/s] 4%|▍ | 1/23 [00:00<00:19, 1.11it/s] 9%|▊ | 2/23 [00:02<00:21, 1.02s/it] 13%|█▎ | 3/23 [00:03<00:21, 1.06s/it] 17%|█▋ | 4/23 [00:04<00:20, 1.08s/it] 22%|██▏ | 5/23 [00:05<00:19, 1.08s/it] 26%|██▌ | 6/23 [00:06<00:18, 1.09s/it] 30%|███ | 7/23 [00:07<00:17, 1.10s/it] 35%|███▍ | 8/23 [00:08<00:16, 1.10s/it] 39%|███▉ | 9/23 [00:09<00:15, 1.10s/it] 43%|████▎ | 10/23 [00:10<00:14, 1.11s/it] 48%|████▊ | 11/23 [00:11<00:13, 1.11s/it] 52%|█████▏ | 12/23 [00:13<00:12, 1.11s/it] 57%|█████▋ | 13/23 [00:14<00:11, 1.11s/it] 61%|██████ | 14/23 [00:15<00:09, 1.11s/it] 65%|██████▌ | 15/23 [00:16<00:08, 1.11s/it] 70%|██████▉ | 16/23 [00:17<00:07, 1.11s/it] 74%|███████▍ | 17/23 [00:18<00:06, 1.11s/it] 78%|███████▊ | 18/23 [00:19<00:05, 1.11s/it] 83%|████████▎ | 19/23 [00:20<00:04, 1.11s/it] 87%|████████▋ | 20/23 [00:21<00:03, 1.11s/it] 91%|█████████▏| 21/23 [00:23<00:02, 1.11s/it] 96%|█████████▌| 22/23 [00:24<00:01, 1.11s/it] 100%|██████████| 23/23 [00:25<00:00, 1.11s/it] 100%|██████████| 23/23 [00:25<00:00, 1.10s/it]
Version Details
- Version ID
392ed0834fbcfdf9a0854e8e1b2ff8126b7951fe9de93d054dcdd6ccd1823d55- Version Created
- October 30, 2024