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philz1337x /multidiffusion-upscaler:88f19697

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
sd_model
string (enum)
juggernaut_reborn.safetensors [338b85bc4f]

Options:

epicrealism_naturalSinRC1VAE.safetensors [84d76a0328], juggernaut_reborn.safetensors [338b85bc4f], juggernaut_final.safetensors

Stable Diffusion model checkpoint
sd_vae
string (enum)
vae-ft-mse-840000-ema-pruned.safetensors

Options:

None, vae-ft-mse-840000-ema-pruned.safetensors

Stable Diffusion VAE checkpoint
image
string
input image
prompt
string
masterpiece, best quality, highres, <lora:more_details:0.5> <lora:SDXLrender_v2.0:1>
Prompt
negative_prompt
string
(worst quality, low quality, normal quality:2) JuggernautNegative-neg
Negative Prompt
width
integer
512
Width of output image
height
integer
512
Height of output image
num_outputs
integer
1

Min: 1

Max: 4

Number of images to output
scheduler
string (enum)
DPM++ 3M SDE Karras

Options:

DPM++ 2M Karras, DPM++ SDE Karras, DPM++ 2M SDE Exponential, DPM++ 2M SDE Karras, Euler a, Euler, LMS, Heun, DPM2, DPM2 a, DPM++ 2S a, DPM++ 2M, DPM++ SDE, DPM++ 2M SDE, DPM++ 2M SDE Heun, DPM++ 2M SDE Heun Karras, DPM++ 2M SDE Heun Exponential, DPM++ 3M SDE, DPM++ 3M SDE Karras, DPM++ 3M SDE Exponential, DPM fast, DPM adaptive, LMS Karras, DPM2 Karras, DPM2 a Karras, DPM++ 2S a Karras, Restart, DDIM, PLMS, UniPC

scheduler
num_inference_steps
integer
18

Min: 1

Max: 100

Number of denoising steps
guidance_scale
number
6

Min: 1

Max: 50

Scale for classifier-free guidance
seed
integer
1337
Random seed. Leave blank to randomize the seed
denoising_strength
number
0.35

Max: 1

Denoising strength. 1.0 corresponds to full destruction of information in init image
clip_stop_at_last_layers
integer
1
CLIP stop at last layers
enable_tiled_diffusion
boolean
True
Enable tiled diffusion
td_method
string (enum)
MultiDiffusion

Options:

MultiDiffusion, Mixture of Diffusers

Tiled diffusion method
td_overwrite_size
boolean
True
Overwrite size
td_keep_input_size
boolean
True
Keep input size
td_image_width
integer
1
Image width
td_image_height
integer
1
Image height
td_tile_width
integer
112
Tile width
td_tile_height
integer
144
Tile height
td_overlap
integer
4
Overlap
td_tile_batch_size
integer
8
Tile batch size
td_upscaler_name
string (enum)
4x-UltraSharp

Options:

None, Lanczos, 4x-UltraSharp, 4x_foolhardy_Remacri, ESRGAN_4x

Upscaler name
td_scale_factor
number
2
Scale factor
td_noise_inverse
boolean
False
Noise inverse
td_noise_inverse_steps
integer
0
Noise inverse steps
td_noise_inverse_renoise_strength
number
0
Noise inverse renoise strength
td_noise_inverse_renoise_kernel
integer
3
Noise inverse renoise kernel
enable_tiled_vae
boolean
True
Enable tiled vae
tv_encoder_tile_size
integer
3072
Encoder tile size
tv_decoder_tile_size
integer
192
Decoder tile size
tv_move_vae_to_gpu
boolean
True
Move vae to gpu(if possible)
tv_fast_decoder
boolean
True
Fast decoder
tv_fast_encoder
boolean
True
Fast encoder
tv_fast_encoder_color_fix
boolean
True
Encoder color fix
enable_controlnet
boolean
True
Enable controlnet
cn_module
string (enum)
tile_resample

Options:

tile_resample

Controlnet module
cn_model
string (enum)
control_v11f1e_sd15_tile

Options:

control_v11f1e_sd15_tile

Controlnet model
cn_weight
number
0.6
Controlnet weight
cn_resize_mode
integer
1
Controlnet resize mode
cn_lowvram
boolean
False
Controlnet lowvram
cn_downsample
number
1
Controlnet downsample
cn_guidance_start
number
0
Controlnet guidance start
cn_guidance_end
number
1
Controlnet guidance end
cn_control_mode
integer
1
Controlnet control mode. 0= Balanced, 1 = My prompt is more important, 2 = ControlNet is more important
cn_pixel_perfect
boolean
True
Controlnet pixel perfect
cn_threshold_a
integer
1
Controlnet threshold a
cn_threshold_b
integer
1
Controlnet threshold b
cn_preprocessor_res
integer
512
Controlnet preprocessor res

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'}