dribnet / dollarpeople

  • Public
  • 1 run

Run dribnet/dollarpeople with an API

Use one of our client libraries to get started quickly. Clicking on a library will take you to the Playground tab where you can tweak different inputs, see the results, and copy the corresponding code to use in your own project.

Input schema

The fields you can use to run this model with an API. If you don't give a value for a field its default value will be used.

Field Type Default value Description
prompt
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.
image
string
Input image for image to image or inpainting mode. If provided, aspect_ratio, width, and height inputs are ignored.
mask
string
Image mask for image inpainting mode. If provided, aspect_ratio, width, and height inputs are ignored.
aspect_ratio
string (enum)
1:1

Options:

1:1, 16:9, 21:9, 3:2, 2:3, 4:5, 5:4, 3:4, 4:3, 9:16, 9:21, custom

Aspect ratio for the generated image. If custom is selected, uses height and width below & will run in bf16 mode
height
integer

Min: 256

Max: 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
width
integer

Min: 256

Max: 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
prompt_strength
number
0.8

Max: 1

Prompt strength when using img2img. 1.0 corresponds to full destruction of information in image
model
string (enum)
dev

Options:

dev, schnell

Which model to run inference with. The dev model performs best with around 28 inference steps but the schnell model only needs 4 steps.
num_outputs
integer
1

Min: 1

Max: 4

Number of outputs to generate
num_inference_steps
integer
28

Min: 1

Max: 50

Number of denoising steps. More steps can give more detailed images, but take longer.
guidance_scale
number
3

Max: 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
seed
integer
Random seed. Set for reproducible generation
output_format
string (enum)
webp

Options:

webp, jpg, png

Format of the output images
output_quality
integer
80

Max: 100

Quality when saving the output images, from 0 to 100. 100 is best quality, 0 is lowest quality. Not relevant for .png outputs
disable_safety_checker
boolean
False
Disable safety checker for generated images.
go_fast
boolean
False
Run faster predictions with model optimized for speed (currently fp8 quantized); disable to run in original bf16
megapixels
string (enum)
1

Options:

1, 0.25

Approximate number of megapixels for generated image
lora_scale
number
1

Min: -1

Max: 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.
extra_lora
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'
extra_lora_scale
number
1

Min: -1

Max: 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.

Output schema

The shape of the response you’ll get when you run this model with an API.

Schema
{
  "type": "array",
  "items": {
    "type": "string",
    "format": "uri"
  },
  "title": "Output"
}