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fermatresearch/high-resolution-controlnet-tile

UPDATE: new upscaling algorithm for a much improved image quality. Fermat.app open-source implementation of an efficient ControlNet 1.1 tile for high-quality upscales. Increase the creativity to encourage hallucination.

Capabilities

Reference Images Negative Prompt Seed

Cost

Community model (estimated from hardware time)

Input Parameters

creativity number

Denoising strength. 1 means total destruction of the original image

Default: 0.35 min: 0.1, max: 1
format string

Format of the output.

Default: "jpg"
jpg png
guess_mode boolean

In this mode, the ControlNet encoder will try best to recognize the content of the input image even if you remove all prompts.

Default: false
guidance_scale number

Scale for classifier-free guidance, should be 0.

Default: 0 min: 0, max: 30
hdr number

HDR improvement over the original image

Default: 0 min: 0, max: 1
image string

Control image for scribble controlnet

lora_details_strength number

Strength of the image's details

Default: 1 min: -5, max: 3
lora_sharpness_strength number

Strength of the image's sharpness. We don't recommend values above 2.

Default: 1.25 min: -5, max: 10
negative_prompt string

Negative prompt

Default: "teeth, tooth, open mouth, longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, mutant"
prompt string

Prompt for the model

resemblance number

Conditioning scale for controlnet

Default: 0.85 min: 0, max: 1
resolution integer

Image resolution

Default: 2560
2048 2560 4096
scheduler string

Choose a scheduler.

Default: "DDIM"
DDIM DPMSolverMultistep K_EULER_ANCESTRAL K_EULER
seed integer

Seed

steps integer

Steps

Default: 8
Version: 8e6a54d7b284 Updated: 6/8/2026 651.7K runs