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batouresearch /instant-paint:f081f007
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
|
An astronaut riding a rainbow unicorn, cinematic, dramatic
|
Input prompt
|
| negative_prompt |
string
|
|
Input Negative Prompt
|
| batched_prompt |
boolean
|
False
|
When active, your prompt will be split by newlines and images will be generated for each individual line
|
| image |
string
|
Input image for img2img
|
|
| num_outputs |
integer
|
1
Min: 1 Max: 4 |
Number of images to output.
|
| scheduler |
string
(enum)
|
LCM
Options: DDIM, DPMSolverMultistep, HeunDiscrete, KarrasDPM, K_EULER_ANCESTRAL, K_EULER, PNDM, LCM |
scheduler
|
| num_inference_steps |
integer
|
6
Min: 1 Max: 20 |
Number of denoising steps
|
| guidance_scale |
number
|
2
Min: 1 Max: 20 |
Scale for classifier-free guidance
|
| prompt_strength |
number
|
0.8
Max: 1 |
Prompt strength when using img2img / inpaint. 1.0 corresponds to full destruction of information in image
|
| seed |
integer
|
Random seed. Leave blank to randomize the seed
|
|
| apply_watermark |
boolean
|
True
|
Applies a watermark to enable determining if an image is generated in downstream applications. If you have other provisions for generating or deploying images safely, you can use this to disable watermarking.
|
| lora_scale |
number
|
0.6
Max: 1 |
LoRA additive scale. Only applicable on trained models.
|
| condition_scale |
number
|
0.5
Max: 1 |
The bigger this number is, the more ControlNet interferes
|
| lora_weights |
string
|
Replicate LoRA weights to use. Leave blank to use the default weights.
|
|
| disable_safety_checker |
boolean
|
True
|
Disable safety checker for generated images. This feature is only available through the API. See [https://replicate.com/docs/how-does-replicate-work#safety](https://replicate.com/docs/how-does-replicate-work#safety)
|
Output schema
The shape of the response you’ll get when you run this model with an API.
Schema
{'items': {'format': 'uri', 'type': 'string'},
'title': 'Output',
'type': 'array'}