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fofr/sdxl-multi-controlnet-lora
Multi-controlnet, lora loading, img2img, inpainting
Capabilities
Cost
Community model (estimated from hardware time)
Input Parameters
| Name | Type | Description | Default | Constraints |
|---|---|---|---|---|
apply_watermark | boolean | 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. | true | — |
controlnet_1 | string | Controlnet | "none" | none edge_canny illusion depth_leres depth_midas soft_edge_pidi soft_edge_hed lineart lineart_anime openpose |
controlnet_1_conditioning_scale | number | How strong the controlnet conditioning is | 0.75 | min: 0, max: 4 |
controlnet_1_end | number | When controlnet conditioning ends | 1 | min: 0, max: 1 |
controlnet_1_image | string (uri) | Input image for first controlnet | — | — |
controlnet_1_start | number | When controlnet conditioning starts | 0 | min: 0, max: 1 |
controlnet_2 | string | Controlnet | "none" | none edge_canny illusion depth_leres depth_midas soft_edge_pidi soft_edge_hed lineart lineart_anime openpose |
controlnet_2_conditioning_scale | number | How strong the controlnet conditioning is | 0.75 | min: 0, max: 4 |
controlnet_2_end | number | When controlnet conditioning ends | 1 | min: 0, max: 1 |
controlnet_2_image | string (uri) | Input image for second controlnet | — | — |
controlnet_2_start | number | When controlnet conditioning starts | 0 | min: 0, max: 1 |
controlnet_3 | string | Controlnet | "none" | none edge_canny illusion depth_leres depth_midas soft_edge_pidi soft_edge_hed lineart lineart_anime openpose |
controlnet_3_conditioning_scale | number | How strong the controlnet conditioning is | 0.75 | min: 0, max: 4 |
controlnet_3_end | number | When controlnet conditioning ends | 1 | min: 0, max: 1 |
controlnet_3_image | string (uri) | Input image for third controlnet | — | — |
controlnet_3_start | number | When controlnet conditioning starts | 0 | min: 0, max: 1 |
disable_safety_checker | boolean | 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) | false | — |
guidance_scale | number | Scale for classifier-free guidance | 7.5 | min: 1, max: 50 |
height | integer | Height of output image | 768 | — |
image | string (uri) | Input image for img2img or inpaint mode | — | — |
lora_scale | number | LoRA additive scale. Only applicable on trained models. | 0.6 | min: 0, max: 1 |
lora_weights | string | Replicate LoRA weights to use. Leave blank to use the default weights. | — | — |
mask | string (uri) | Input mask for inpaint mode. Black areas will be preserved, white areas will be inpainted. | — | — |
negative_prompt | string | Negative Prompt | "" | — |
num_inference_steps | integer | Number of denoising steps | 30 | min: 1, max: 500 |
num_outputs | integer | Number of images to output | 1 | min: 1, max: 4 |
prompt | string | Input prompt | "An astronaut riding a rainbow unicorn" | — |
prompt_strength | number | Prompt strength when using img2img / inpaint. 1.0 corresponds to full destruction of information in image | 0.8 | min: 0, max: 1 |
refine | string | Which refine style to use | "no_refiner" | no_refiner base_image_refiner |
refine_steps | integer | For base_image_refiner, the number of steps to refine, defaults to num_inference_steps | — | — |
scheduler | string | scheduler | "K_EULER" | DDIM DPMSolverMultistep HeunDiscrete KarrasDPM K_EULER_ANCESTRAL K_EULER PNDM |
seed | integer | Random seed. Leave blank to randomize the seed | — | — |
sizing_strategy | string | Decide how to resize images – use width/height, resize based on input image or control image | "width_height" | width_height input_image controlnet_1_image controlnet_2_image controlnet_3_image mask_image |
width | integer | Width of output image | 768 | — |
apply_watermark boolean 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.
true controlnet_1 string Controlnet
"none" controlnet_1_conditioning_scale number How strong the controlnet conditioning is
0.75 min: 0, max: 4 controlnet_1_end number When controlnet conditioning ends
1 min: 0, max: 1 controlnet_1_image string Input image for first controlnet
controlnet_1_start number When controlnet conditioning starts
0 min: 0, max: 1 controlnet_2 string Controlnet
"none" controlnet_2_conditioning_scale number How strong the controlnet conditioning is
0.75 min: 0, max: 4 controlnet_2_end number When controlnet conditioning ends
1 min: 0, max: 1 controlnet_2_image string Input image for second controlnet
controlnet_2_start number When controlnet conditioning starts
0 min: 0, max: 1 controlnet_3 string Controlnet
"none" controlnet_3_conditioning_scale number How strong the controlnet conditioning is
0.75 min: 0, max: 4 controlnet_3_end number When controlnet conditioning ends
1 min: 0, max: 1 controlnet_3_image string Input image for third controlnet
controlnet_3_start number When controlnet conditioning starts
0 min: 0, max: 1 disable_safety_checker boolean 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)
false guidance_scale number Scale for classifier-free guidance
7.5 min: 1, max: 50 height integer Height of output image
768 image string Input image for img2img or inpaint mode
lora_scale number LoRA additive scale. Only applicable on trained models.
0.6 min: 0, max: 1 lora_weights string Replicate LoRA weights to use. Leave blank to use the default weights.
mask string Input mask for inpaint mode. Black areas will be preserved, white areas will be inpainted.
negative_prompt string Negative Prompt
"" num_inference_steps integer Number of denoising steps
30 min: 1, max: 500 num_outputs integer Number of images to output
1 min: 1, max: 4 prompt string Input prompt
"An astronaut riding a rainbow unicorn" prompt_strength number Prompt strength when using img2img / inpaint. 1.0 corresponds to full destruction of information in image
0.8 min: 0, max: 1 refine string Which refine style to use
"no_refiner" refine_steps integer For base_image_refiner, the number of steps to refine, defaults to num_inference_steps
scheduler string scheduler
"K_EULER" seed integer Random seed. Leave blank to randomize the seed
sizing_strategy string Decide how to resize images – use width/height, resize based on input image or control image
"width_height" width integer Width of output image
768 89eb212b3d13 Updated: 2/26/2026 217.9K runs