Elena AI Image Generator

Discover the Elena AI Image Generator, a powerful tool for generating and editing images. Let's dive in and explore what this AI model can do for you!

Platform: Replicate

Text-to-Image GenerationImage InpaintingLoRA AdaptationImage-to-Image Translation

20 runs

H100

License Check Required

🚀Function Overview

Generates and modifies images using diffusion processes with customizable parameters for aspect ratios, resolution, prompt strength, and LoRA scaling.

Key Features

Text-to-image generation using detailed prompts
Image-to-image transformation with input images
Inpainting functionality via mask inputs
Aspect ratio and custom dimension controls
Dual model support (dev/schnell) with step optimization
LoRA integration for specialized style adaptation
Adjustable output quality and format options
Safety checker toggle for generated content

Use Cases

•Creating custom artwork from textual descriptions
•Editing photos through inpainting (object removal/addition)
•Generating professional profile pictures
•Experimenting with artistic styles using LoRA models
•Rapid prototyping of visual concepts

⚙️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": "Ultra-realistic headshot of a young woman named Elenaedhec, aged 20 standing in a sunlit, high-end corporate office with floor-to-ceiling windows and soft background bokeh. She wears a perfectly tailored dark navy blazer over a minimalist white silk blouse, no visible logos. Her posture is relaxed yet assertive, with arms gently crossed or hands lightly in front. Her long, brushed chestnut or brunette hair flows naturally, with subtle waves. She has clear skin with soft, natural makeup that enhances her features without exaggeration. Her expression is calm, confident, and intelligent — radiating leadership, warmth, and charisma. DSLR-quality photo with ultra-sharp focus on the eyes, soft natural lighting on the face, and a shallow depth of field. The mood is premium, timeless, professional — ideal for a top-tier LinkedIn profile photo, C-suite profile, or magazine feature.",
  "go_fast": false,
  "lora_scale": 1,
  "megapixels": "1",
  "num_outputs": 1,
  "aspect_ratio": "5:4",
  "output_format": "webp",
  "guidance_scale": 2,
  "output_quality": 80,
  "prompt_strength": 0.8,
  "extra_lora_scale": 1,
  "num_inference_steps": 28
}

Output Results

https://replicate.delivery/xezq/IZOftiqCgFVKXShn8i3waHXoV7VHlbfq4RJ5gBvw78fgel6SB/out-0.webp

Quick Actions

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Technical Specifications

Hardware Type: H100
Run Count: 20
Commercial Use: Unknown/Restricted
Platform: Replicate

Related Keywords

Text-to-Image GenerationImage InpaintingLoRA AdaptationImage-to-Image TranslationCustom ArtworkPhoto EditingVisual Concept Prototyping

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