jamesliuzx/manga 🖼️🔢📝❓✓ → 🖼️
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Example Output
Prompt:
"Moonlit mansion In the style of TOK."
Output
Performance Metrics
14.95s
Prediction Time
15.59s
Total Time
All Input Parameters
{
"width": 1024,
"height": 1024,
"prompt": "Moonlit mansion In the style of TOK.",
"refine": "no_refiner",
"scheduler": "K_EULER",
"lora_scale": 0.6,
"preview_size": 256,
"guidance_scale": 7.5,
"apply_watermark": true,
"high_noise_frac": 0.8,
"negative_prompt": "Text blurring, face blurring",
"prompt_strength": 0.8,
"num_inference_steps": 50
}
Input Parameters
- mask
- Input mask for inpaint mode. Black areas will be preserved, white areas will be inpainted.
- seed
- Random seed. Leave blank to randomize the seed
- image
- Input image for img2img or inpaint mode
- width
- Width of output image
- height
- Height of output image
- prompt
- Input prompt
- refine
- Which refine style to use
- scheduler
- scheduler
- lora_scale
- LoRA additive scale. Only applicable on trained models.
- preview_size
- Size of preview image in pixels
- refine_steps
- For base_image_refiner, the number of steps to refine, defaults to num_inference_steps
- preview_steps
- Number of steps to preview
- guidance_scale
- Scale for classifier-free guidance
- apply_watermark
- Applies a watermark to enable determining if an image is generated in downstream applications. If you have other provisions for generating or deploying images safely, you can use this to disable watermarking.
- high_noise_frac
- For expert_ensemble_refiner, the fraction of noise to use
- negative_prompt
- Input Negative Prompt
- prompt_strength
- Prompt strength when using img2img / inpaint. 1.0 corresponds to full destruction of information in image
- replicate_weights
- Replicate LoRA weights to use. Leave blank to use the default weights.
- num_inference_steps
- Number of denoising steps
Output Schema
Output
Version Details
- Version ID
f0bdba9facf64f87b4beac6757180b3a5f8f9751c1cd6c03f22d289fe2ed2cf4- Version Created
- September 27, 2023