vladikowens/vladik 🖼️🔢❓📝✓ → 🖼️
About
Example Output
Prompt:
"tok A professional and dynamic scene of a digital marketing expert giving a conference on a large stage in front of 500 attentive audience members. The expert, a confident and well-dressed individual, is speaking passionately into a microphone, exuding expertise and authority. The scene is captured from a front-facing perspective, showcasing the expert standing center stage with a clear view of their entire figure and the LED screen behind them. The shot focuses on a closeup of the expert's face, ensuring it is identical to the reference image, with clear and highly detailed features, a focused and determined expression, and perfect symmetry. Behind the expert, a massive LED screen displays a detailed and visually appealing sales funnel graphic, showcasing stages like Awareness, Interest, Decision, and Action. The stage is well-lit with modern lighting, and the audience is seated in a large auditorium, fully engaged and listening intently. The atmosphere is professional, inspiring, and futuristic, with a focus on the expert as the central figure. High-quality, realistic, and detailed rendering, emphasizing the expert's confidence, the clarity and consistency of their facial features, and the modern, high-tech environment. The face must always remain in closeup, ensuring it is the focal point of the image"
Output
Performance Metrics
7.48s
Prediction Time
7.49s
Total Time
All Input Parameters
{
"model": "dev",
"prompt": "tok A professional and dynamic scene of a digital marketing expert giving a conference on a large stage in front of 500 attentive audience members. The expert, a confident and well-dressed individual, is speaking passionately into a microphone, exuding expertise and authority. The scene is captured from a front-facing perspective, showcasing the expert standing center stage with a clear view of their entire figure and the LED screen behind them. The shot focuses on a closeup of the expert's face, ensuring it is identical to the reference image, with clear and highly detailed features, a focused and determined expression, and perfect symmetry. Behind the expert, a massive LED screen displays a detailed and visually appealing sales funnel graphic, showcasing stages like Awareness, Interest, Decision, and Action. The stage is well-lit with modern lighting, and the audience is seated in a large auditorium, fully engaged and listening intently. The atmosphere is professional, inspiring, and futuristic, with a focus on the expert as the central figure. High-quality, realistic, and detailed rendering, emphasizing the expert's confidence, the clarity and consistency of their facial features, and the modern, high-tech environment. The face must always remain in closeup, ensuring it is the focal point of the image",
"go_fast": false,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "png",
"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
Weights already loaded Loaded LoRAs in 0.02s Using seed: 8834 Prompt: tok A professional and dynamic scene of a digital marketing expert giving a conference on a large stage in front of 500 attentive audience members. The expert, a confident and well-dressed individual, is speaking passionately into a microphone, exuding expertise and authority. The scene is captured from a front-facing perspective, showcasing the expert standing center stage with a clear view of their entire figure and the LED screen behind them. The shot focuses on a closeup of the expert's face, ensuring it is identical to the reference image, with clear and highly detailed features, a focused and determined expression, and perfect symmetry. Behind the expert, a massive LED screen displays a detailed and visually appealing sales funnel graphic, showcasing stages like Awareness, Interest, Decision, and Action. The stage is well-lit with modern lighting, and the audience is seated in a large auditorium, fully engaged and listening intently. The atmosphere is professional, inspiring, and futuristic, with a focus on the expert as the central figure. High-quality, realistic, and detailed rendering, emphasizing the expert's confidence, the clarity and consistency of their facial features, and the modern, high-tech environment. The face must always remain in closeup, ensuring it is the focal point of the image [!] txt2img mode 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:06, 4.03it/s] 7%|▋ | 2/28 [00:00<00:05, 4.56it/s] 11%|█ | 3/28 [00:00<00:05, 4.31it/s] 14%|█▍ | 4/28 [00:00<00:05, 4.19it/s] 18%|█▊ | 5/28 [00:01<00:05, 4.12it/s] 21%|██▏ | 6/28 [00:01<00:05, 4.09it/s] 25%|██▌ | 7/28 [00:01<00:05, 4.07it/s] 29%|██▊ | 8/28 [00:01<00:04, 4.06it/s] 32%|███▏ | 9/28 [00:02<00:04, 4.05it/s] 36%|███▌ | 10/28 [00:02<00:04, 4.05it/s] 39%|███▉ | 11/28 [00:02<00:04, 4.04it/s] 43%|████▎ | 12/28 [00:02<00:03, 4.04it/s] 46%|████▋ | 13/28 [00:03<00:03, 4.04it/s] 50%|█████ | 14/28 [00:03<00:03, 4.04it/s] 54%|█████▎ | 15/28 [00:03<00:03, 4.04it/s] 57%|█████▋ | 16/28 [00:03<00:02, 4.04it/s] 61%|██████ | 17/28 [00:04<00:02, 4.03it/s] 64%|██████▍ | 18/28 [00:04<00:02, 4.03it/s] 68%|██████▊ | 19/28 [00:04<00:02, 4.03it/s] 71%|███████▏ | 20/28 [00:04<00:01, 4.03it/s] 75%|███████▌ | 21/28 [00:05<00:01, 4.04it/s] 79%|███████▊ | 22/28 [00:05<00:01, 4.04it/s] 82%|████████▏ | 23/28 [00:05<00:01, 4.03it/s] 86%|████████▌ | 24/28 [00:05<00:00, 4.04it/s] 89%|████████▉ | 25/28 [00:06<00:00, 4.03it/s] 93%|█████████▎| 26/28 [00:06<00:00, 4.02it/s] 96%|█████████▋| 27/28 [00:06<00:00, 4.03it/s] 100%|██████████| 28/28 [00:06<00:00, 4.03it/s] 100%|██████████| 28/28 [00:06<00:00, 4.06it/s] Total safe images: 1 out of 1
Version Details
- Version ID
15f402f01d268e2033c83cc729f176b228d55206ad6cf16afaa75fe0602352f2- Version Created
- March 4, 2025