aihecs/cleopatre_ntc_ihecs πΌοΈπ’βπβ β πΌοΈ
About
Example Output
Prompt:
"cleopatre_ntc_ihecs. "A young woman lounging in a lavish private jet, flaunting her wealth with a brash, provocative attitude. Sheβs wearing a revealing, designer outfit and sitting casually with her legs stretched across plush leather seats. Around her, the cabin is filled with luxury items: designer bags, champagne bottles, and expensive accessories. She holds a glass of champagne, her posture bold and carefree, exuding a sense of entitlement and indulgence. The jetβs interior is sleek and modern, with large windows showing a clear blue sky, adding to the atmosphere of extravagant, unapologetic luxury.""
Output
Performance Metrics
35.05s
Prediction Time
36.32s
Total Time
All Input Parameters
{
"image": "https://replicate.delivery/pbxt/LnzY4ETmmmtU4e9HFWdiKX9XJ4WC1fjyqiiQnnpj6n6BgLyZ/IMG_0254.png",
"model": "dev",
"prompt": "cleopatre_ntc_ihecs. \"A young woman lounging in a lavish private jet, flaunting her wealth with a brash, provocative attitude. Sheβs wearing a revealing, designer outfit and sitting casually with her legs stretched across plush leather seats. Around her, the cabin is filled with luxury items: designer bags, champagne bottles, and expensive accessories. She holds a glass of champagne, her posture bold and carefree, exuding a sense of entitlement and indulgence. The jetβs interior is sleek and modern, with large windows showing a clear blue sky, adding to the atmosphere of extravagant, unapologetic luxury.\"",
"lora_scale": 1,
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 3.5,
"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: 15053 Prompt: cleopatre_ntc_ihecs. "A young woman lounging in a lavish private jet, flaunting her wealth with a brash, provocative attitude. Sheβs wearing a revealing, designer outfit and sitting casually with her legs stretched across plush leather seats. Around her, the cabin is filled with luxury items: designer bags, champagne bottles, and expensive accessories. She holds a glass of champagne, her posture bold and carefree, exuding a sense of entitlement and indulgence. The jetβs interior is sleek and modern, with large windows showing a clear blue sky, adding to the atmosphere of extravagant, unapologetic luxury." [!] Resizing input image from 2360x1640 to 2368x1648 [!] img2img mode [!] Using dev model for img2img Using dev model Loaded LoRAs in 0.59s 0%| | 0/23 [00:00<?, ?it/s] 4%|β | 1/23 [00:01<00:26, 1.18s/it] 9%|β | 2/23 [00:02<00:27, 1.33s/it] 13%|ββ | 3/23 [00:04<00:27, 1.37s/it] 17%|ββ | 4/23 [00:05<00:26, 1.39s/it] 22%|βββ | 5/23 [00:06<00:25, 1.41s/it] 26%|βββ | 6/23 [00:08<00:24, 1.41s/it] 30%|βββ | 7/23 [00:09<00:22, 1.42s/it] 35%|ββββ | 8/23 [00:11<00:21, 1.42s/it] 39%|ββββ | 9/23 [00:12<00:19, 1.42s/it] 43%|βββββ | 10/23 [00:14<00:18, 1.43s/it] 48%|βββββ | 11/23 [00:15<00:17, 1.43s/it] 52%|ββββββ | 12/23 [00:16<00:15, 1.43s/it] 57%|ββββββ | 13/23 [00:18<00:14, 1.43s/it] 61%|ββββββ | 14/23 [00:19<00:12, 1.43s/it] 65%|βββββββ | 15/23 [00:21<00:11, 1.43s/it] 70%|βββββββ | 16/23 [00:22<00:09, 1.43s/it] 74%|ββββββββ | 17/23 [00:24<00:08, 1.43s/it] 78%|ββββββββ | 18/23 [00:25<00:07, 1.43s/it] 83%|βββββββββ | 19/23 [00:26<00:05, 1.43s/it] 87%|βββββββββ | 20/23 [00:28<00:04, 1.43s/it] 91%|ββββββββββ| 21/23 [00:29<00:02, 1.43s/it] 96%|ββββββββββ| 22/23 [00:31<00:01, 1.43s/it] 100%|ββββββββββ| 23/23 [00:32<00:00, 1.43s/it] 100%|ββββββββββ| 23/23 [00:32<00:00, 1.42s/it]
Version Details
- Version ID
5df2da8e2769d6de5cbd400bd3d3b39033884438926621583cc06228faa8de4c- Version Created
- October 15, 2024