Carlaluiza Image Generation

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Platform: Replicate

Image GenerationImage InpaintingLoRA Adaptation

253 runs

H100

License Check Required

🚀Function Overview

Generates, edits, or inpaints images based on text prompts and input images, with extensive customization options for resolution, style, and output quality.

Key Features

Text-to-image generation with prompt customization
Image-to-image transformation
Mask-based inpainting capabilities
Adjustable aspect ratio and resolution
Multiple model variants for quality/speed trade-offs
LoRA adapter support for style/object customization
Configurable denoising steps and guidance scale
Safety checker toggle for content filtering

Use Cases

•Marketing and editorial image creation
•Photo editing and enhancement
•Artistic image generation
•Product concept visualization
•Character and scene design

⚙️Input Parameters

prompt

string

Prompt for generated image. If you include the `trigger_word` used in the training process you are more likely to activate the trained object, style, or concept in the resulting image.

image

string

Input image for image to image or inpainting mode. If provided, aspect_ratio, width, and height inputs are ignored.

mask

string

Image mask for image inpainting mode. If provided, aspect_ratio, width, and height inputs are ignored.

aspect_ratio

string

Aspect ratio for the generated image. If custom is selected, uses height and width below & will run in bf16 mode

height

integer

Height of generated image. Only works if `aspect_ratio` is set to custom. Will be rounded to nearest multiple of 16. Incompatible with fast generation

width

integer

Width of generated image. Only works if `aspect_ratio` is set to custom. Will be rounded to nearest multiple of 16. Incompatible with fast generation

prompt_strength

number

Prompt strength when using img2img. 1.0 corresponds to full destruction of information in image

model

string

Which model to run inference with. The dev model performs best with around 28 inference steps but the schnell model only needs 4 steps.

num_outputs

integer

Number of outputs to generate

num_inference_steps

integer

Number of denoising steps. More steps can give more detailed images, but take longer.

guidance_scale

number

Guidance scale for the diffusion process. Lower values can give more realistic images. Good values to try are 2, 2.5, 3 and 3.5

seed

integer

Random seed. Set for reproducible generation

output_format

string

Format of the output images

output_quality

integer

Quality when saving the output images, from 0 to 100. 100 is best quality, 0 is lowest quality. Not relevant for .png outputs

disable_safety_checker

boolean

Disable safety checker for generated images.

go_fast

boolean

Run faster predictions with model optimized for speed (currently fp8 quantized); disable to run in original bf16

megapixels

string

Approximate number of megapixels for generated image

lora_scale

number

Determines how strongly the main LoRA should be applied. Sane results between 0 and 1 for base inference. For go_fast we apply a 1.5x multiplier to this value; we've generally seen good performance when scaling the base value by that amount. You may still need to experiment to find the best value for your particular lora.

extra_lora

string

Load LoRA weights. Supports Replicate models in the format <owner>/<username> or <owner>/<username>/<version>, HuggingFace URLs in the format huggingface.co/<owner>/<model-name>, CivitAI URLs in the format civitai.com/models/<id>[/<model-name>], or arbitrary .safetensors URLs from the Internet. For example, 'fofr/flux-pixar-cars'

extra_lora_scale

number

Determines how strongly the extra LoRA should be applied. Sane results between 0 and 1 for base inference. For go_fast we apply a 1.5x multiplier to this value; we've generally seen good performance when scaling the base value by that amount. You may still need to experiment to find the best value for your particular lora.

💡Usage Examples

Example 1

Input Parameters

{
  "model": "dev",
  "prompt": "carlaluiza CLOC[Elegant semi-midsize woman with long, wavy black hair, waist length hair, and fair skin tone] [Slightly leaning forward, looking confidently at the camera] [Minimalist studio backdrop in neutral gray tones] [Eye-level angle, close-up marketing campaign photo] [High ticket luxury mentor style] [Flawless makeup with bold lashes, sculpted brows, matte brown lips; soft blush; long brown nails; cozy dark green turtleneck sweater layered over a sleek burgundy oversized blazer; [Large gold hoop earrings, layered gold necklaces, gold bracelets, and visible forearm tattoo] [Soft knit and wool textures balanced with sleek hair and glossy product packaging under diffused studio lighting] [Color palette in ivory, soft gray, gold, blush pink, and nude tones] [Premium 2025s mentor editorial aesthetic with empowered beauty tone] [No clutter, no harsh shadows, no blur on the model, no nudity, no bad nails, no short hair] [Canon EOS R5 with RF 100mm f/2.8L Macro IS lens]",
  "go_fast": false,
  "lora_scale": 1,
  "megapixels": "1",
  "num_outputs": 1,
  "aspect_ratio": "3:4",
  "output_format": "png",
  "guidance_scale": 3,
  "output_quality": 80,
  "prompt_strength": 0.8,
  "extra_lora_scale": 1,
  "num_inference_steps": 28
}

Output Results

https://replicate.delivery/xezq/hcGVlX0Pt6bqF5p2bE4zH7Rise6edEWtu8fRU7eVohZTe4klC/out-0.png

Quick Actions

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Technical Specifications

Hardware Type: H100
Run Count: 253
Commercial Use: Unknown/Restricted
Platform: Replicate

Related Keywords

Text-to-image generationImage InpaintingLoRA adapter supportImage-to-image transformationAdjustable aspect ratioMultiple model variantsMarketing and editorial image creationPhoto editing and enhancement

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