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cloneofsimo /hotshot-xl-lora-controlnet:2bbeec97
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
|
Hi there doggo!
|
The main prompt that guides the image generation.
|
| negative_prompt |
string
|
|
A negative prompt to avoid certain features in the generated images.
|
| width |
integer
|
672
|
The width of the generated images.
|
| height |
integer
|
384
|
The height of the generated images.
|
| original_width |
integer
|
1920
|
The width of the `original_size` of images. If `original_size` is not the same as `target_size` the image will appear to be down- or upsampled.
`original_size` defaults to `(width, height)` if not specified. Part of SDXL's micro-conditioning as
explained in section 2.2 of
[https://huggingface.co/papers/2307.01952](https://huggingface.co/papers/2307.01952).
|
| original_height |
integer
|
1080
|
The `original_size height` of the images.
|
| target_width |
integer
|
512
|
The `target_size width` of the images.
|
| target_height |
integer
|
512
|
The `target_size height` of the images.
|
| steps |
integer
|
30
|
The number of steps for the prediction.
|
| video_length |
integer
|
8
|
The length of the video in frames.
|
| video_duration |
integer
|
1000
|
The duration of the video in milliseconds.
|
| hf_lora_url |
string
|
The URL for LoRA weights.
|
|
| control_type |
string
(enum)
|
Options: canny, depth |
The type of control net to use for conditional generation.
|
| gif |
string
|
Input GIF for controlnet condition.
|
|
| control_guidance_start |
number
|
0
|
The start of the control guidance.
|
| control_guidance_end |
number
|
1
|
The end of the control guidance.
|
| controlnet_conditioning_scale |
number
|
0.7
|
The scale of the controlnet conditioning.
|
| replicate_weights_url |
string
|
Replicate LoRA weights to use. Leave blank to use the default weights.
|
Output schema
The shape of the response you’ll get when you run this model with an API.
Schema
{'format': 'uri', 'title': 'Output', 'type': 'string'}