biggpt1/irtv-mosque 🖼️🔢❓📝✓ → 🖼️
About
Example Output
"
A breathtaking aerial view of Vladikavkaz, Russia, featuring the historic Mukhtarov Mosque as the focal point. The mosque, with its distinctive twin minarets and intricate Oriental-style detailing, stands gracefully among the city's architectural blend of old and modern buildings. The Terek River winds through the city, reflecting the golden sunlight and flanked by lush, tree-lined streets.
In the background, the majestic Ossetian mountains rise, their rugged peaks standing tall against a brilliant blue sky. Soft clouds hover near the summits, adding depth to the composition. The city's streets bustle with activity, with visible parks, bridges, and classic European-style facades complementing the modern urban structures.
Above the city, several aerostats float gently in the distance, their soft, rounded forms contrasting with the rigid geometry of the mosque and cityscape. The sunlight casts a warm glow over the entire scene, enhancing the rich colors of the buildings and natural elements. The atmosphere is serene yet dynamic, capturing the harmony between Vladikavkaz's historical heritage and its evolving modernity
"Output



Performance Metrics
All Input Parameters
{
"model": "dev",
"prompt": "A breathtaking aerial view of Vladikavkaz, Russia, featuring the historic Mukhtarov Mosque as the focal point. The mosque, with its distinctive twin minarets and intricate Oriental-style detailing, stands gracefully among the city's architectural blend of old and modern buildings. The Terek River winds through the city, reflecting the golden sunlight and flanked by lush, tree-lined streets.\n\nIn the background, the majestic Ossetian mountains rise, their rugged peaks standing tall against a brilliant blue sky. Soft clouds hover near the summits, adding depth to the composition. The city's streets bustle with activity, with visible parks, bridges, and classic European-style facades complementing the modern urban structures.\n\nAbove the city, several aerostats float gently in the distance, their soft, rounded forms contrasting with the rigid geometry of the mosque and cityscape. The sunlight casts a warm glow over the entire scene, enhancing the rich colors of the buildings and natural elements. The atmosphere is serene yet dynamic, capturing the harmony between Vladikavkaz's historical heritage and its evolving modernity",
"go_fast": false,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 4,
"aspect_ratio": "21:9",
"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
free=28233142050816 Downloading weights 2025-03-05T19:18:49Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp9n_o9xb0/weights url=https://replicate.delivery/xezq/3eE9l6fB4KvNVkpOOEn88wPVvfyGvWQzvmLlcuCTJIi1WKroA/trained_model.tar 2025-03-05T19:18:54Z | INFO | [ Complete ] dest=/tmp/tmp9n_o9xb0/weights size="344 MB" total_elapsed=5.061s url=https://replicate.delivery/xezq/3eE9l6fB4KvNVkpOOEn88wPVvfyGvWQzvmLlcuCTJIi1WKroA/trained_model.tar Downloaded weights in 5.09s Loaded LoRAs in 7.74s Using seed: 48447 Prompt: A breathtaking aerial view of Vladikavkaz, Russia, featuring the historic Mukhtarov Mosque as the focal point. The mosque, with its distinctive twin minarets and intricate Oriental-style detailing, stands gracefully among the city's architectural blend of old and modern buildings. The Terek River winds through the city, reflecting the golden sunlight and flanked by lush, tree-lined streets. In the background, the majestic Ossetian mountains rise, their rugged peaks standing tall against a brilliant blue sky. Soft clouds hover near the summits, adding depth to the composition. The city's streets bustle with activity, with visible parks, bridges, and classic European-style facades complementing the modern urban structures. Above the city, several aerostats float gently in the distance, their soft, rounded forms contrasting with the rigid geometry of the mosque and cityscape. The sunlight casts a warm glow over the entire scene, enhancing the rich colors of the buildings and natural elements. The atmosphere is serene yet dynamic, capturing the harmony between Vladikavkaz's historical heritage and its evolving modernity [!] txt2img mode 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:39, 1.47s/it] 7%|▋ | 2/28 [00:02<00:26, 1.03s/it] 11%|█ | 3/28 [00:03<00:24, 1.04it/s] 14%|█▍ | 4/28 [00:03<00:22, 1.08it/s] 18%|█▊ | 5/28 [00:04<00:20, 1.10it/s] 21%|██▏ | 6/28 [00:05<00:19, 1.11it/s] 25%|██▌ | 7/28 [00:06<00:18, 1.12it/s] 29%|██▊ | 8/28 [00:07<00:17, 1.13it/s] 32%|███▏ | 9/28 [00:08<00:16, 1.13it/s] 36%|███▌ | 10/28 [00:09<00:15, 1.13it/s] 39%|███▉ | 11/28 [00:10<00:14, 1.13it/s] 43%|████▎ | 12/28 [00:10<00:14, 1.13it/s] 46%|████▋ | 13/28 [00:11<00:13, 1.14it/s] 50%|█████ | 14/28 [00:12<00:12, 1.14it/s] 54%|█████▎ | 15/28 [00:13<00:11, 1.14it/s] 57%|█████▋ | 16/28 [00:14<00:10, 1.14it/s] 61%|██████ | 17/28 [00:15<00:09, 1.14it/s] 64%|██████▍ | 18/28 [00:16<00:08, 1.14it/s] 68%|██████▊ | 19/28 [00:17<00:07, 1.14it/s] 71%|███████▏ | 20/28 [00:18<00:07, 1.14it/s] 75%|███████▌ | 21/28 [00:18<00:06, 1.14it/s] 79%|███████▊ | 22/28 [00:19<00:05, 1.14it/s] 82%|████████▏ | 23/28 [00:20<00:04, 1.14it/s] 86%|████████▌ | 24/28 [00:21<00:03, 1.14it/s] 89%|████████▉ | 25/28 [00:22<00:02, 1.14it/s] 93%|█████████▎| 26/28 [00:23<00:01, 1.14it/s] 96%|█████████▋| 27/28 [00:24<00:00, 1.14it/s] 100%|██████████| 28/28 [00:25<00:00, 1.14it/s] 100%|██████████| 28/28 [00:25<00:00, 1.12it/s] Total safe images: 4 out of 4
Version Details
- Version ID
c5d4b8730f71a23a0a101fccc210579dc0a1f8ea495b7b917f8afb0a0c45ea4b- Version Created
- March 5, 2025