abubakar0111/nouman 🖼️🔢❓📝✓ → 🖼️

▶️ 156 runs 📅 Dec 2024 ⚙️ Cog 0.11.1

About

Example Output

Prompt:

"portrait of nouman “A Studio Ghibli-inspired 2D animation featuring a man with a short beard, exuding a timeless and elegant appearance. He is dressed in a tailored suit that subtly catches the light, highlighting its refined details. The animation showcases smooth, lifelike movements, with his attire gently swaying and shimmering naturally. The background is a richly detailed, painterly landscape with warm, soft tones that create a serene and dreamy atmosphere. Intricate hand-painted textures blend seamlessly with cinematic highlights and shadows, adding depth and dimension. The lighting is thoughtfully placed to emphasize the character’s intellectual aura, making him the focal point in this beautifully atmospheric and immersive world.”"

Output

Performance Metrics

8.62s Prediction Time

8.66s Total Time

All Input Parameters

{
  "model": "dev",
  "prompt": "portrait of nouman “A Studio Ghibli-inspired 2D animation featuring a man with a short beard, exuding a timeless and elegant appearance. He is dressed in a tailored suit that subtly catches the light, highlighting its refined details. The animation showcases smooth, lifelike movements, with his attire gently swaying and shimmering naturally. The background is a richly detailed, painterly landscape with warm, soft tones that create a serene and dreamy atmosphere. Intricate hand-painted textures blend seamlessly with cinematic highlights and shadows, adding depth and dimension. The lighting is thoughtfully placed to emphasize the character’s intellectual aura, making him the focal point in this beautifully atmospheric and immersive world.”\n",
  "go_fast": false,
  "lora_scale": 1,
  "megapixels": "1",
  "num_outputs": 1,
  "aspect_ratio": "1:1",
  "output_format": "webp",
  "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

2024-12-29 06:06:06.778 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2024-12-29 06:06:06.779 | DEBUG    | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA:   0%|          | 0/304 [00:00<?, ?it/s]
Applying LoRA:  91%|█████████▏| 278/304 [00:00<00:00, 2777.32it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2639.05it/s]
2024-12-29 06:06:06.894 | SUCCESS  | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.12s
free=29084134096896
Downloading weights
2024-12-29T06:06:06Z | INFO  | [ Initiating ] chunk_size=150M dest=/tmp/tmpecf5zm_6/weights url=https://replicate.delivery/xezq/ETvVApXYVQqZGdZVxoZV6vouRmGR0X3KnnrSqrxxjtZ2C6fJA/trained_model.tar
2024-12-29T06:06:09Z | INFO  | [ Complete ] dest=/tmp/tmpecf5zm_6/weights size="258 MB" total_elapsed=2.124s url=https://replicate.delivery/xezq/ETvVApXYVQqZGdZVxoZV6vouRmGR0X3KnnrSqrxxjtZ2C6fJA/trained_model.tar
Downloaded weights in 2.15s
2024-12-29 06:06:09.045 | INFO     | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/26cd87a23234edcf
2024-12-29 06:06:09.127 | INFO     | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded
2024-12-29 06:06:09.127 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2024-12-29 06:06:09.128 | DEBUG    | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA:   0%|          | 0/304 [00:00<?, ?it/s]
Applying LoRA:  91%|█████████▏| 278/304 [00:00<00:00, 2778.49it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2639.30it/s]
2024-12-29 06:06:09.243 | SUCCESS  | fp8.lora_loading:load_lora:539 - LoRA applied in 0.2s
Using seed: 23073
0it [00:00, ?it/s]
1it [00:00,  8.27it/s]
2it [00:00,  5.81it/s]
3it [00:00,  5.28it/s]
4it [00:00,  5.08it/s]
5it [00:00,  4.96it/s]
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7it [00:01,  4.84it/s]
8it [00:01,  4.81it/s]
9it [00:01,  4.80it/s]
10it [00:02,  4.78it/s]
11it [00:02,  4.77it/s]
12it [00:02,  4.77it/s]
13it [00:02,  4.78it/s]
14it [00:02,  4.77it/s]
15it [00:03,  4.77it/s]
16it [00:03,  4.75it/s]
17it [00:03,  4.75it/s]
18it [00:03,  4.76it/s]
19it [00:03,  4.76it/s]
20it [00:04,  4.76it/s]
21it [00:04,  4.75it/s]
22it [00:04,  4.75it/s]
23it [00:04,  4.76it/s]
24it [00:04,  4.75it/s]
25it [00:05,  4.75it/s]
26it [00:05,  4.75it/s]
27it [00:05,  4.74it/s]
28it [00:05,  4.74it/s]
28it [00:05,  4.83it/s]
Total safe images: 1 out of 1

Version Details

Version ID: 6a0ca8a97dc9957c436b97f93b26bd45fa2ea030c4acd3177ce927ed2e85ffa0
Version Created: December 29, 2024

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