swk23/vader 🖼️🔢❓📝✓ → 🖼️

▶️ 216 runs 📅 Oct 2024 ⚙️ Cog 0.9.26
image-inpainting image-to-image lora lora-famous-person lora-person text-to-image

About

Example Output

Prompt:

""A close-up of Darth Vader's iconic helmet in a dark, shadowy room. The polished black surface reflects faint glimmers of light, emphasizing the intricate details of the mask. His red-lit eyes glow faintly, exuding a menacing presence, while subtle wisps of mist curl around the base of his helmet. The room's darkness frames his imposing visage, creating an atmosphere of intimidation and mystery.""

Output

Example output

Performance Metrics

11.41s Prediction Time
14.20s Total Time
All Input Parameters
{
  "model": "dev",
  "prompt": "\"A close-up of Darth Vader's iconic helmet in a dark, shadowy room. The polished black surface reflects faint glimmers of light, emphasizing the intricate details of the mask. His red-lit eyes glow faintly, exuding a menacing presence, while subtle wisps of mist curl around the base of his helmet. The room's darkness frames his imposing visage, creating an atmosphere of intimidation and mystery.\"",
  "go_fast": false,
  "lora_scale": 1,
  "megapixels": "1",
  "num_outputs": 1,
  "aspect_ratio": "21:9",
  "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: arrayItems Type: stringItems Format: uri

Example Execution Logs
2025-01-07 04:25:19.067 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2025-01-07 04:25:19.068 | DEBUG    | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA:   0%|          | 0/304 [00:00<?, ?it/s]
Applying LoRA:  90%|█████████ | 275/304 [00:00<00:00, 2734.59it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2643.06it/s]
2025-01-07 04:25:19.183 | SUCCESS  | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.12s
free=28915602481152
Downloading weights
2025-01-07T04:25:19Z | INFO  | [ Initiating ] chunk_size=150M dest=/tmp/tmp6ylwg7vd/weights url=https://replicate.delivery/yhqm/JKAlEJBElCqxGNf5qaH0wcufp2fZ23XYLIiTVJ1DKAKK5tMnA/trained_model.tar
2025-01-07T04:25:24Z | INFO  | [ Complete ] dest=/tmp/tmp6ylwg7vd/weights size="172 MB" total_elapsed=5.592s url=https://replicate.delivery/yhqm/JKAlEJBElCqxGNf5qaH0wcufp2fZ23XYLIiTVJ1DKAKK5tMnA/trained_model.tar
Downloaded weights in 5.62s
2025-01-07 04:25:24.801 | INFO     | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/b8333114e6bacd62
2025-01-07 04:25:24.871 | INFO     | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded
2025-01-07 04:25:24.871 | DEBUG    | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2025-01-07 04:25:24.872 | DEBUG    | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA:   0%|          | 0/304 [00:00<?, ?it/s]
Applying LoRA:  90%|█████████ | 275/304 [00:00<00:00, 2739.17it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2647.00it/s]
2025-01-07 04:25:24.987 | SUCCESS  | fp8.lora_loading:load_lora:539 - LoRA applied in 0.19s
Using seed: 12705
0it [00:00, ?it/s]
1it [00:00,  9.19it/s]
2it [00:00,  6.45it/s]
3it [00:00,  5.89it/s]
4it [00:00,  5.66it/s]
5it [00:00,  5.53it/s]
6it [00:01,  5.38it/s]
7it [00:01,  5.37it/s]
8it [00:01,  5.36it/s]
9it [00:01,  5.35it/s]
10it [00:01,  5.34it/s]
11it [00:01,  5.31it/s]
12it [00:02,  5.28it/s]
13it [00:02,  5.28it/s]
14it [00:02,  5.29it/s]
15it [00:02,  5.31it/s]
16it [00:02,  5.31it/s]
17it [00:03,  5.29it/s]
18it [00:03,  5.30it/s]
19it [00:03,  5.29it/s]
20it [00:03,  5.29it/s]
21it [00:03,  5.29it/s]
22it [00:04,  5.30it/s]
23it [00:04,  5.28it/s]
24it [00:04,  5.29it/s]
25it [00:04,  5.30it/s]
26it [00:04,  5.29it/s]
27it [00:05,  5.31it/s]
28it [00:05,  5.31it/s]
28it [00:05,  5.38it/s]
Total safe images: 1 out of 1
Version Details
Version ID
b78e5a9f0e79033b003074bcece2f0b85a915af6cd8aed82ea47578e9ee34b8f
Version Created
October 13, 2024
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