gabrielbarrientos99/real_nesuko_zenitsu 🖼️🔢❓📝✓ → 🖼️

▶️ 40 runs 📅 Dec 2024 ⚙️ Cog 0.11.1

About

Crea imágenes de fusión entre Nesuko y Zenitsu, con realismo. Usa "NESUKO" Y "ZENITSU" como disparadores

Example Output

Prompt:

"A young boy who embodies the traits of ZENITSU and NEZUKO, with short, slightly wavy hair that blends ZENITSU's bright yellow with NEZUKO's dark brown and pink highlights, giving it a vibrant and unique appearance. His eyes are sharp yet expressive, a mix of ZENITSU's golden hue and NEZUKO's soft pink tones, adding depth and warmth to his gaze. His facial features are youthful and balanced, with a calm yet playful expression. He wears a modernized kimono-style outfit that combines ZENITSU's lightning pattern in yellow and black with NEZUKO's floral motifs in pink and dark tones, tied with a sleek sash. The background features a tranquil bamboo forest with soft sunlight streaming through, casting a gentle glow that enhances his radiant and serene presence."

Output

Performance Metrics

6.27s Prediction Time

6.28s Total Time

All Input Parameters

{
  "model": "dev",
  "prompt": "A young boy who embodies the traits of ZENITSU and NEZUKO, with short, slightly wavy hair that blends ZENITSU's bright yellow with NEZUKO's dark brown and pink highlights, giving it a vibrant and unique appearance. His eyes are sharp yet expressive, a mix of ZENITSU's golden hue and NEZUKO's soft pink tones, adding depth and warmth to his gaze. His facial features are youthful and balanced, with a calm yet playful expression. He wears a modernized kimono-style outfit that combines ZENITSU's lightning pattern in yellow and black with NEZUKO's floral motifs in pink and dark tones, tied with a sleek sash. The background features a tranquil bamboo forest with soft sunlight streaming through, casting a gentle glow that enhances his radiant and serene presence.\n\n\n",
  "go_fast": false,
  "lora_scale": 1,
  "megapixels": "1",
  "num_outputs": 1,
  "aspect_ratio": "9:16",
  "output_format": "jpg",
  "guidance_scale": 3,
  "output_quality": 80,
  "prompt_strength": 0.8,
  "extra_lora_scale": 1,
  "num_inference_steps": 28
}

Input Parameters

mask Type: string: Image mask for image inpainting mode. If provided, aspect_ratio, width, and height inputs are ignored.
seed Type: integer: Random seed. Set for reproducible generation
image Type: string: Input image for image to image or inpainting mode. If provided, aspect_ratio, width, and height inputs are ignored.
model Default: dev: 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 Type: integerRange: 256 - 1440: 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 Type: integerRange: 256 - 1440: 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) Type: string: 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 Type: booleanDefault: false: Run faster predictions with model optimized for speed (currently fp8 quantized); disable to run in original bf16
extra_lora Type: string: 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 Type: numberDefault: 1Range: -1 - 3: 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 Default: 1: Approximate number of megapixels for generated image
num_outputs Type: integerDefault: 1Range: 1 - 4: Number of outputs to generate
aspect_ratio Default: 1:1: Aspect ratio for the generated image. If custom is selected, uses height and width below & will run in bf16 mode
output_format Default: webp: Format of the output images
guidance_scale Type: numberDefault: 3Range: 0 - 10: 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 Type: integerDefault: 80Range: 0 - 100: 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 Type: numberDefault: 0.8Range: 0 - 1: Prompt strength when using img2img. 1.0 corresponds to full destruction of information in image
extra_lora_scale Type: numberDefault: 1Range: -1 - 3: 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 Type: string: 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 Type: integerDefault: 28Range: 1 - 50: Number of denoising steps. More steps can give more detailed images, but take longer.
disable_safety_checker Type: booleanDefault: false: Disable safety checker for generated images.

Output Schema

Output

Type: array • Items Type: string • Items Format: uri

Example Execution Logs

2024-12-25 06:46:06.553 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2024-12-25 06:46:06.553 | DEBUG    | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA:   0%|          | 0/304 [00:00<?, ?it/s]
Applying LoRA:  95%|█████████▍| 288/304 [00:00<00:00, 2870.35it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2821.72it/s]
2024-12-25 06:46:06.661 | SUCCESS  | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s
2024-12-25 06:46:06.663 | INFO     | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/56646d7cadf1e77f
2024-12-25 06:46:06.784 | INFO     | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded
2024-12-25 06:46:06.785 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2024-12-25 06:46:06.785 | DEBUG    | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA:   0%|          | 0/304 [00:00<?, ?it/s]
Applying LoRA:  95%|█████████▍| 288/304 [00:00<00:00, 2870.82it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2821.77it/s]
2024-12-25 06:46:06.893 | SUCCESS  | fp8.lora_loading:load_lora:539 - LoRA applied in 0.23s
Using seed: 9656
0it [00:00, ?it/s]
1it [00:00,  8.50it/s]
2it [00:00,  5.95it/s]
3it [00:00,  5.43it/s]
4it [00:00,  5.21it/s]
5it [00:00,  5.10it/s]
6it [00:01,  5.02it/s]
7it [00:01,  4.97it/s]
8it [00:01,  4.94it/s]
9it [00:01,  4.94it/s]
10it [00:01,  4.93it/s]
11it [00:02,  4.92it/s]
12it [00:02,  4.91it/s]
13it [00:02,  4.91it/s]
14it [00:02,  4.91it/s]
15it [00:02,  4.90it/s]
16it [00:03,  4.90it/s]
17it [00:03,  4.90it/s]
18it [00:03,  4.90it/s]
19it [00:03,  4.90it/s]
20it [00:03,  4.90it/s]
21it [00:04,  4.90it/s]
22it [00:04,  4.90it/s]
23it [00:04,  4.90it/s]
24it [00:04,  4.89it/s]
25it [00:05,  4.89it/s]
26it [00:05,  4.89it/s]
27it [00:05,  4.89it/s]
28it [00:05,  4.89it/s]
28it [00:05,  4.97it/s]
Total safe images: 1 out of 1

Version Details

Version ID: a46a2aac057f905b63ce78e85998cf2d7d8237876d8310514644da6cbc4f02be
Version Created: December 25, 2024

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