tarot-cards/rider-waite 🖼️🔢❓📝✓ → 🖼️

▶️ 4.0K runs 📅 Feb 2025 ⚙️ Cog 0.13.7

About

A Flux fine-tune of the Rider-Waite tarot card deck (1909)

Example Output

Prompt:

"A tarot card depiciting the golden gate bridge in san francisco, in the style of tarot-cards/rider-waite. The labels "

Output

Performance Metrics

16.92s Prediction Time

20.94s Total Time

All Input Parameters

{
  "model": "dev",
  "prompt": "A tarot card depiciting the golden gate bridge in san francisco, in the style of tarot-cards/rider-waite. The labels ",
  "go_fast": false,
  "lora_scale": 1,
  "megapixels": "1",
  "num_outputs": 1,
  "aspect_ratio": "2:3",
  "output_format": "webp",
  "guidance_scale": 3,
  "output_quality": 100,
  "prompt_strength": 0.8,
  "extra_lora_scale": 1,
  "num_inference_steps": 50
}

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

free=28878264950784
Downloading weights
2025-02-05T21:05:51Z | INFO  | [ Initiating ] chunk_size=150M dest=/tmp/tmpnrpvpgbt/weights url=https://replicate.delivery/xezq/dcfGkB2JfHk12kdnZBZfA1ZiaDsQtgE1pixk3CIeHZtGwZxQB/trained_model.tar
2025-02-05T21:05:54Z | INFO  | [ Complete ] dest=/tmp/tmpnrpvpgbt/weights size="172 MB" total_elapsed=2.956s url=https://replicate.delivery/xezq/dcfGkB2JfHk12kdnZBZfA1ZiaDsQtgE1pixk3CIeHZtGwZxQB/trained_model.tar
Downloaded weights in 2.98s
Loaded LoRAs in 3.55s
Using seed: 51667
Prompt: A tarot card depiciting the golden gate bridge in san francisco, in the style of tarot-cards/rider-waite. The labels
[!] txt2img mode
  0%|          | 0/50 [00:00<?, ?it/s]
  2%|▏         | 1/50 [00:00<00:12,  4.07it/s]
  4%|▍         | 2/50 [00:00<00:10,  4.59it/s]
  6%|▌         | 3/50 [00:00<00:10,  4.36it/s]
  8%|▊         | 4/50 [00:00<00:10,  4.23it/s]
 10%|█         | 5/50 [00:01<00:10,  4.17it/s]
 12%|█▏        | 6/50 [00:01<00:10,  4.14it/s]
 14%|█▍        | 7/50 [00:01<00:10,  4.11it/s]
 16%|█▌        | 8/50 [00:01<00:10,  4.10it/s]
 18%|█▊        | 9/50 [00:02<00:10,  4.09it/s]
 20%|██        | 10/50 [00:02<00:09,  4.07it/s]
 22%|██▏       | 11/50 [00:02<00:10,  3.64it/s]
 24%|██▍       | 12/50 [00:03<00:10,  3.61it/s]
 26%|██▌       | 13/50 [00:03<00:10,  3.43it/s]
 28%|██▊       | 14/50 [00:03<00:10,  3.36it/s]
 30%|███       | 15/50 [00:03<00:10,  3.30it/s]
 32%|███▏      | 16/50 [00:04<00:10,  3.35it/s]
 34%|███▍      | 17/50 [00:04<00:09,  3.40it/s]
 36%|███▌      | 18/50 [00:04<00:09,  3.43it/s]
 38%|███▊      | 19/50 [00:05<00:08,  3.74it/s]
 40%|████      | 20/50 [00:05<00:08,  3.58it/s]
 42%|████▏     | 21/50 [00:05<00:08,  3.53it/s]
 44%|████▍     | 22/50 [00:05<00:07,  3.52it/s]
 46%|████▌     | 23/50 [00:06<00:07,  3.47it/s]
 48%|████▊     | 24/50 [00:06<00:07,  3.46it/s]
 50%|█████     | 25/50 [00:06<00:07,  3.50it/s]
 52%|█████▏    | 26/50 [00:07<00:06,  3.54it/s]
 54%|█████▍    | 27/50 [00:07<00:06,  3.73it/s]
 56%|█████▌    | 28/50 [00:07<00:05,  3.83it/s]
 58%|█████▊    | 29/50 [00:07<00:05,  3.89it/s]
 60%|██████    | 30/50 [00:08<00:05,  3.94it/s]
 62%|██████▏   | 31/50 [00:08<00:04,  3.96it/s]
 64%|██████▍   | 32/50 [00:08<00:04,  3.97it/s]
 66%|██████▌   | 33/50 [00:08<00:04,  4.00it/s]
 68%|██████▊   | 34/50 [00:09<00:03,  4.02it/s]
 70%|███████   | 35/50 [00:09<00:03,  4.04it/s]
 72%|███████▏  | 36/50 [00:09<00:03,  4.04it/s]
 74%|███████▍  | 37/50 [00:09<00:03,  4.04it/s]
 76%|███████▌  | 38/50 [00:10<00:02,  4.04it/s]
 78%|███████▊  | 39/50 [00:10<00:02,  4.05it/s]
 80%|████████  | 40/50 [00:10<00:02,  4.05it/s]
 82%|████████▏ | 41/50 [00:10<00:02,  4.06it/s]
 84%|████████▍ | 42/50 [00:11<00:01,  4.07it/s]
 86%|████████▌ | 43/50 [00:11<00:01,  4.06it/s]
 88%|████████▊ | 44/50 [00:11<00:01,  4.06it/s]
 90%|█████████ | 45/50 [00:11<00:01,  4.06it/s]
 92%|█████████▏| 46/50 [00:12<00:00,  4.04it/s]
 94%|█████████▍| 47/50 [00:12<00:00,  4.05it/s]
 96%|█████████▌| 48/50 [00:12<00:00,  4.03it/s]
 98%|█████████▊| 49/50 [00:12<00:00,  4.03it/s]
100%|██████████| 50/50 [00:12<00:00,  4.05it/s]
100%|██████████| 50/50 [00:12<00:00,  3.85it/s]
Total safe images: 1 out of 1

Version Details

Version ID: 6d77a07ef88e8a09389385cb14d98b12629a4b23b0537b01dfeb833c32827546
Version Created: February 5, 2025

Run on Replicate →