Neon-Impressionism-Flux Open-source AI Model - Freely Generate Stunning Neon Impressionist-style Images

Neon Impressionism Flux

Developed by strangerzonehf

A diffusion model based on LoRA technology, specifically designed for generating neon impressionist-style images

Image Generation Open Source License:Openrail #Impasto texture impressionism #High-contrast colors #Dynamic brushstroke expression

Downloads 266

Release Time : 2/12/2025

Model Overview

This model fine-tunes the base diffusion model using LoRA technology to generate artworks with neon colors and impressionist brushstroke styles based on text descriptions.

Model Features

Neon Impressionist Style

Specially optimized for generating impressionist-style images with vibrant neon colors and thick brushstrokes

LoRA Fine-tuning Technology

Utilizes LoRA technology for efficient fine-tuning of the base diffusion model, preserving original capabilities while enabling specific style generation

Multi-size Support

Supports multiple output sizes, with special optimization for 3:2 and 1:1 aspect ratio images

Model Capabilities

Text-to-image generation

Art style transformation

High-resolution image generation

Use Cases

Digital art creation

Impressionist-style food image generation

Generates food images with neon colors and impressionist style based on text descriptions

As shown in the example hamburger image, featuring vivid color contrasts and thick brushstrokes

Abstract portrait creation

Generates expressive abstract character portraits

As shown in the example profile portrait, using contrasting colors and dynamic brushstrokes to convey emotional tension

Creative design

Landscape art creation

Generates trees and natural landscapes with unique styles

As shown in the example tree image, using colorful blocks to form the canopy

Sports scene representation

Captures the dynamism and energy of motion

As shown in the example surfer image, enhancing movement through color swirls

🚀 Neon-Impressionism-Flux

This is a text-to-image model based on LoRA and Diffusers, capable of generating vivid and colorful paintings in the style of Neon Impressionism.

🚀 Quick Start

Installation

import torch
from pipelines import DiffusionPipeline

base_model = "black-forest-labs/FLUX.1-dev"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)

lora_repo = "strangerzonehf/Halftone-Recraft-Flux"
trigger_word = "Neon Impressionism"  
pipe.load_lora_weights(lora_repo)

device = torch.device("cuda")
pipe.to(device)

Usage

You should use Neon Impressionism to trigger the image generation.

✨ Features

This model can generate various types of images in the Neon Impressionism style, such as hamburgers, person profiles, trees, and surfers. The generated images are characterized by bright colors, thick brushstrokes, and a sense of movement and energy.

📦 Installation

import torch
from pipelines import DiffusionPipeline

base_model = "black-forest-labs/FLUX.1-dev"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)

lora_repo = "strangerzonehf/Halftone-Recraft-Flux"
trigger_word = "Neon Impressionism"  
pipe.load_lora_weights(lora_repo)

device = torch.device("cuda")
pipe.to(device)

💻 Usage Examples

Basic Usage

import torch
from pipelines import DiffusionPipeline

base_model = "black-forest-labs/FLUX.1-dev"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)

lora_repo = "strangerzonehf/Halftone-Recraft-Flux"
trigger_word = "Neon Impressionism"  
pipe.load_lora_weights(lora_repo)

device = torch.device("cuda")
pipe.to(device)

# Generate an image
prompt = "Neon Impressionism, a beautiful landscape"
image = pipe(prompt).images[0]
image.save("generated_image.png")

📚 Documentation

Image Processing Parameters

Parameter	Value	Parameter	Value
LR Scheduler	constant	Noise Offset	0.03
Optimizer	AdamW	Multires Noise Discount	0.1
Network Dim	64	Multires Noise Iterations	10
Network Alpha	32	Repeat & Steps	27 & 3400
Epoch	22	Save Every N Epochs	1

Best Dimensions & Inference

Dimensions	Aspect Ratio	Recommendation
1280 x 832	3:2	Best
1024 x 1024	1:1	Default

Inference Range

Recommended Inference Steps: 30–35

Labeling

Labeling: januspro-en(natural language & English)

Training Data

Total Images Used for Training : 46

📄 License

This model is licensed under creativeml-openrail-m.

Download model

Weights for this model are available in Safetensors format.

Download them in the Files & versions tab.

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