Skin Retouching Lora

Prompt
make the subjects skin details more prominent and natural
Prompt
make the subjects skin details more prominent and natural
Prompt
make the subjects skin details more prominent and natural
Prompt
make the subjects skin details more prominent and natural
Prompt
make the subjects skin details more prominent and natural

Model description

This is an image-editing LoRA. Provide an input image and an instruction describing the edit. Trigger word: use make the subjects skin details more prominent and natural in your instructions for best results. The examples below show input → output for different instructions.

Trigger word

Include make the subjects skin details more prominent and natural in your edit instruction, for example:

make the subjects skin details more prominent and natural <your edit instruction here>

Gallery

Example 1

Example 1

Prompt: make the subjects skin details more prominent and natural

Input: Input 1

Example 2

Example 2

Prompt: make the subjects skin details more prominent and natural

Input: Input 2

Example 3

Example 3

Prompt: make the subjects skin details more prominent and natural

Input: Input 3

Example 4

Example 4

Prompt: make the subjects skin details more prominent and natural

Input: Input 4

Example 5

Example 5

Prompt: make the subjects skin details more prominent and natural

Input: Input 5

LoRA scale

The gallery was generated with lora_scale=1.0. You can tune this when running inference (e.g. lower for a subtler effect, higher for a stronger style).

Use on Replicate

import replicate

output = replicate.run(
    "prunaai/p-image-edit-lora:17651bd22e8c151cdb13a97b0f8554dce1e7238cd0a18cf90bc237ac5f0bc067",
    input={
        "images": ["https://example.com/input.png"],
        "prompt": "make the subjects skin details more prominent and natural your edit instruction",
        "lora_weights": "https://huggingface.co/davidberenstein1957/p-image-edit-skin-retouching-lora/resolve/main/weights.safetensors",
        "lora_scale": 1.0,
        "hf_api_token": "your-hf-token",
    }
)
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