lightweight-ai/model3_4 🖼️🔢📝✓❓ → 🖼️
About
Example Output
Prompt:
"A bohemian-style female travel blogger with sun-kissed skin and messy beach waves"
Output
Performance Metrics
4.35s
Prediction Time
403.37s
Total Time
All Input Parameters
{
"loras": [],
"width": 1024,
"height": 1024,
"prompt": "A bohemian-style female travel blogger with sun-kissed skin and messy beach waves",
"inpaint": false,
"scheduler": "K_EULER",
"lora_scales": [],
"num_outputs": 1,
"output_format": "png",
"guidance_scale": 3.5,
"output_quality": 100,
"negative_prompt": "",
"prompt_strength": 0.8,
"num_inference_steps": 28
}
Input Parameters
- mask
- Upload a mask image for inpainting. White areas (255) indicate regions to be inpainted, while black areas (0) will be preserved from the original image.
- seed
- Random seed. Set for reproducible generation
- image
- Upload an image for inpainting. This will be the base image that will be partially modified.
- loras
- Lora list (Realism, Karina, IU)
- width
- Width of output image
- height
- Height of output image
- prompt
- Prompt for generated image
- inpaint
- scheduler
- scheduler
- controlnet
- lora_scales
- Lora scales
- num_outputs
- Number of images to output.
- control_type
- Control type
- nsfw_chekcer
- sketch_image
- Control image
- control_image
- Control image
- low_threshold
- output_format
- Format of the output images
- guidance_scale
- high_threshold
- 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
- negative_prompt
- negative prompt
- prompt_strength
- Prompt strength (or denoising strength) when using image to image. 1.0 corresponds to full destruction of information in image.
- control_strength
- num_inference_steps
- Number of inference steps
Output Schema
Output
Example Execution Logs
Model base : https://sg-model-store.s3.ap-northeast-2.amazonaws.com/SDXL/base/sd_xl_base_1.0.safetensors Using seed: 42889 Prompt: A bohemian-style female travel blogger with sun-kissed skin and messy beach waves 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:08, 3.29it/s] 11%|█ | 3/28 [00:00<00:03, 6.97it/s] 14%|█▍ | 4/28 [00:00<00:03, 7.40it/s] 18%|█▊ | 5/28 [00:00<00:02, 7.69it/s] 21%|██▏ | 6/28 [00:00<00:02, 7.90it/s] 25%|██▌ | 7/28 [00:00<00:02, 8.04it/s] 29%|██▊ | 8/28 [00:01<00:02, 8.15it/s] 32%|███▏ | 9/28 [00:01<00:02, 8.22it/s] 36%|███▌ | 10/28 [00:01<00:02, 8.26it/s] 39%|███▉ | 11/28 [00:01<00:02, 8.29it/s] 43%|████▎ | 12/28 [00:01<00:01, 8.31it/s] 46%|████▋ | 13/28 [00:01<00:01, 8.33it/s] 50%|█████ | 14/28 [00:01<00:01, 8.33it/s] 54%|█████▎ | 15/28 [00:01<00:01, 8.33it/s] 57%|█████▋ | 16/28 [00:02<00:01, 8.33it/s] 61%|██████ | 17/28 [00:02<00:01, 8.33it/s] 64%|██████▍ | 18/28 [00:02<00:01, 8.33it/s] 68%|██████▊ | 19/28 [00:02<00:01, 8.33it/s] 71%|███████▏ | 20/28 [00:02<00:00, 8.34it/s] 75%|███████▌ | 21/28 [00:02<00:00, 8.33it/s] 79%|███████▊ | 22/28 [00:02<00:00, 8.33it/s] 82%|████████▏ | 23/28 [00:02<00:00, 8.34it/s] 86%|████████▌ | 24/28 [00:02<00:00, 8.34it/s] 89%|████████▉ | 25/28 [00:03<00:00, 8.34it/s] 93%|█████████▎| 26/28 [00:03<00:00, 8.33it/s] 96%|█████████▋| 27/28 [00:03<00:00, 8.32it/s] 100%|██████████| 28/28 [00:03<00:00, 8.31it/s] 100%|██████████| 28/28 [00:03<00:00, 8.06it/s] GPU 0: NVIDIA L40S Memory Usage: 12141.0MB / 46068.0MB GPU Utilization: 99.0%
Version Details
- Version ID
3db8401934ab8847047c76cce766bc7390a54ae0a5342e42da8b27098b78f5ca- Version Created
- March 4, 2025