gigidiva/kiki πΌοΈπ’βπβ β πΌοΈ
About
Example Output
Prompt:
"A romantic scene of an Asian couple sitting on a white couch in a cozy, modern living room. The man is wearing a light denim jacket over a white t-shirt, sitting behind and wrapping his arms gently around the womanβs waist. He rests his cheek near her temple, eyes closed in a peaceful moment. The woman, named kiki, has honey-toned skin, round face, long eye lashes, double clear eye lid. She wears a white short-sleeved t-shirt and high-waisted denim shorts, leaning slightly into him and smiling warmly while looking at the camera. The background features soft lighting, wooden shelves, and evoking a romantic, cinematic atmosphere like a scene from a love story film."
Output
Performance Metrics
8.16s
Prediction Time
8.35s
Total Time
All Input Parameters
{
"model": "dev",
"prompt": "A romantic scene of an Asian couple sitting on a white couch in a cozy, modern living room. The man is wearing a light denim jacket over a white t-shirt, sitting behind and wrapping his arms gently around the womanβs waist. He rests his cheek near her temple, eyes closed in a peaceful moment. The woman, named kiki, has honey-toned skin, round face, long eye lashes, double clear eye lid. She wears a white short-sleeved t-shirt and high-waisted denim shorts, leaning slightly into him and smiling warmly while looking at the camera. The background features soft lighting, wooden shelves, and evoking a romantic, cinematic atmosphere like a scene from a love story film.\n",
"go_fast": false,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 1,
"aspect_ratio": "16:9",
"output_format": "jpg",
"guidance_scale": 2.53,
"output_quality": 100,
"prompt_strength": 0.79,
"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
Loaded LoRAs in 0.62s Using seed: 31520 Prompt: A romantic scene of an Asian couple sitting on a white couch in a cozy, modern living room. The man is wearing a light denim jacket over a white t-shirt, sitting behind and wrapping his arms gently around the womanβs waist. He rests his cheek near her temple, eyes closed in a peaceful moment. The woman, named kiki, has honey-toned skin, round face, long eye lashes, double clear eye lid. She wears a white short-sleeved t-shirt and high-waisted denim shorts, leaning slightly into him and smiling warmly while looking at the camera. The background features soft lighting, wooden shelves, and evoking a romantic, cinematic atmosphere like a scene from a love story film. [!] txt2img mode 0%| | 0/28 [00:00<?, ?it/s] 4%|β | 1/28 [00:00<00:07, 3.78it/s] 7%|β | 2/28 [00:00<00:06, 4.29it/s] 11%|β | 3/28 [00:00<00:06, 4.05it/s] 14%|ββ | 4/28 [00:01<00:06, 3.95it/s] 18%|ββ | 5/28 [00:01<00:05, 3.89it/s] 21%|βββ | 6/28 [00:01<00:05, 3.86it/s] 25%|βββ | 7/28 [00:01<00:05, 3.84it/s] 29%|βββ | 8/28 [00:02<00:05, 3.83it/s] 32%|ββββ | 9/28 [00:02<00:04, 3.82it/s] 36%|ββββ | 10/28 [00:02<00:04, 3.81it/s] 39%|ββββ | 11/28 [00:02<00:04, 3.81it/s] 43%|βββββ | 12/28 [00:03<00:04, 3.80it/s] 46%|βββββ | 13/28 [00:03<00:03, 3.80it/s] 50%|βββββ | 14/28 [00:03<00:03, 3.80it/s] 54%|ββββββ | 15/28 [00:03<00:03, 3.80it/s] 57%|ββββββ | 16/28 [00:04<00:03, 3.80it/s] 61%|ββββββ | 17/28 [00:04<00:02, 3.80it/s] 64%|βββββββ | 18/28 [00:04<00:02, 3.80it/s] 68%|βββββββ | 19/28 [00:04<00:02, 3.80it/s] 71%|ββββββββ | 20/28 [00:05<00:02, 3.80it/s] 75%|ββββββββ | 21/28 [00:05<00:01, 3.80it/s] 79%|ββββββββ | 22/28 [00:05<00:01, 3.80it/s] 82%|βββββββββ | 23/28 [00:06<00:01, 3.80it/s] 86%|βββββββββ | 24/28 [00:06<00:01, 3.80it/s] 89%|βββββββββ | 25/28 [00:06<00:00, 3.80it/s] 93%|ββββββββββ| 26/28 [00:06<00:00, 3.80it/s] 96%|ββββββββββ| 27/28 [00:07<00:00, 3.80it/s] 100%|ββββββββββ| 28/28 [00:07<00:00, 3.80it/s] 100%|ββββββββββ| 28/28 [00:07<00:00, 3.83it/s] Total safe images: 1 out of 1
Version Details
- Version ID
0b6bd0f26d25376c86a54c5f15d2db7ec7301d40ae19da40df06d40461643f1b- Version Created
- April 22, 2025