derickson/ds-01 🖼️🔢❓📝✓ → 🖼️

▶️ 20 runs 📅 Apr 2025 ⚙️ Cog 0.14.3
image-inpainting image-to-image lora text-to-image

About

learning to fine tune a lora

Example Output

Prompt:

"in the style of bromdarksun25, a painting of a muscled warrior brandishing a spear in a gladiator arena, he wears a mix of bone, metal, and obsidian armor pieces. he is intimidating and yelling"

Output

Example output

Performance Metrics

4.18s Prediction Time
4.19s Total Time
All Input Parameters
{
  "image": "https://replicate.delivery/pbxt/MtFE70ID5jCM94NPTlef1yncdGosXWUfpPuY9b5NYOcUzAg1/templatebrom.jpg",
  "model": "dev",
  "prompt": "in the style of bromdarksun25, a painting of a muscled warrior brandishing a spear in a gladiator arena, he wears a mix of bone, metal, and obsidian armor pieces. he is intimidating and yelling",
  "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": 0.5,
  "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
Weights already loaded
Loaded LoRAs in 0.02s
Using seed: 61695
Prompt: in the style of bromdarksun25, a painting of a muscled warrior brandishing a spear in a gladiator arena, he wears a mix of bone, metal, and obsidian armor pieces. he is intimidating and yelling
Input image size: 1024x1024
[!] Resizing input image from 1024x1024 to 1024x1024
[!] img2img mode
  0%|          | 0/14 [00:00<?, ?it/s]
  7%|▋         | 1/14 [00:00<00:02,  4.76it/s]
 14%|█▍        | 2/14 [00:00<00:02,  4.16it/s]
 21%|██▏       | 3/14 [00:00<00:02,  4.00it/s]
 29%|██▊       | 4/14 [00:00<00:02,  3.93it/s]
 36%|███▌      | 5/14 [00:01<00:02,  3.89it/s]
 43%|████▎     | 6/14 [00:01<00:02,  3.87it/s]
 50%|█████     | 7/14 [00:01<00:01,  3.85it/s]
 57%|█████▋    | 8/14 [00:02<00:01,  3.84it/s]
 64%|██████▍   | 9/14 [00:02<00:01,  3.83it/s]
 71%|███████▏  | 10/14 [00:02<00:01,  3.83it/s]
 79%|███████▊  | 11/14 [00:02<00:00,  3.83it/s]
 86%|████████▌ | 12/14 [00:03<00:00,  3.82it/s]
 93%|█████████▎| 13/14 [00:03<00:00,  3.82it/s]
100%|██████████| 14/14 [00:03<00:00,  3.82it/s]
100%|██████████| 14/14 [00:03<00:00,  3.88it/s]
Total safe images: 1 out of 1
Version Details
Version ID
ca4f2ed73bc8b5d9a97c49a349fc13fa50e736b15e9396eae8ea0f0634b089fd
Version Created
April 24, 2025
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