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Nobira Image Generation

Unleash your creativity with Nobira, an advanced image generation model. Ready to experience the power of AI? Start your journey here!

Platform: Replicate
Image GenerationInpaintingLoRA IntegrationCustom Aspect Ratio
74 runs
H100
License Check Required

🚀Function Overview

A diffusion-based model for creating and modifying images using text prompts image inputs masks and granular controls over artistic attributes like aspect ratio LoRA weights and generation speed.

Key Features

  • Text-to-image generation from detailed prompts
  • Image inpainting with mask support
  • Custom aspect ratios and dimensions
  • LoRA weight integration for style control
  • Adjustable generation speed modes (fast/standard)

Use Cases

  • Creating custom artwork from text descriptions
  • Editing existing photos via inpainting
  • Generating marketing visuals with brand-specific styles
  • Developing game assets with consistent artistic themes

⚙️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": "Full-body professional portrait of a woman named Nobira, sitting gracefully on a simple white plastic garden chair. She has a genuine, warm smile and radiates happiness. Her shoulder length, neat dark hair frames her face. She's wearing form-fitting light blue skinny jeans paired with a sleeveless, fitted royal blue v-neck top that complements her figure. On her feet are classic white high-heeled pumps with clean, minimalist lines. Her hands rest naturally and comfortably on her thighs in a relaxed pose. The background features a smooth, neutral gray backdrop that provides clean separation. Professional studio lighting creates soft, even illumination with gentle shadows that enhance dimension and depth. The lighting setup includes key lighting with fill light to minimize harsh shadows, creating a polished commercial photography aesthetic. Her fingers are bare of any jewelry or rings. Shot with professional camera settings for sharp detail and beautiful bokeh",
  "go_fast": false,
  "lora_scale": 1,
  "megapixels": "1",
  "num_outputs": 1,
  "aspect_ratio": "1:1",
  "output_format": "jpg",
  "guidance_scale": 3,
  "output_quality": 90,
  "prompt_strength": 0.8,
  "extra_lora_scale": 1,
  "num_inference_steps": 28
}

Output Results

https://replicate.delivery/xezq/EcDgVmk9zgbKBJyHaXygFa9BiZuYSyx2tpMtE4FarobTFnLF/out-0.jpg

Quick Actions

Technical Specifications

Hardware Type
H100
Run Count
74
Commercial Use
Unknown/Restricted
Platform
Replicate

Related Keywords

Text-to-image generationImage inpaintingCustom aspect ratiosLoRA integrationAdjustable generation speedCreating custom artworkEditing existing photosGenerating marketing visuals