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A newer version of the Gradio SDK is available: 5.39.0

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metadata
title: FLUX Fast & Furious
emoji: πŸ–ΌπŸ†
colorFrom: purple
colorTo: red
sdk: gradio
sdk_version: 5.35.0
app_file: app.py
pinned: false
license: openrail++
short_description: FLUX 8 Step Fast & High Quality Mode

I'll create comprehensive documentation for this FLUX Fast & Furious image generation code in both English and Korean.

English Documentation

FLUX: Fast & Furious - Hyper-Speed Image Generation

This application implements an accelerated version of the FLUX.1-dev image generation model, optimized by ByteDance's AutoML team using their Hyper-SD technology to achieve high-quality image generation in just 8 steps instead of the typical 20-50 steps.

Key Features

  1. Hyper-Speed Generation

    • Utilizes Hyper-SD LoRA (Low-Rank Adaptation) technology from ByteDance
    • Reduces inference steps from 20-50 to just 6-25 steps (default: 8)
    • Maintains high image quality while dramatically reducing generation time
    • Optimized for CUDA with TF32 precision enabled for maximum performance
  2. Neon-Themed User Interface

    • Custom cyberpunk-inspired design with glowing neon effects
    • Animated hover effects and dynamic visual feedback
    • Dark theme with blue, cyan, and magenta color accents
    • Responsive layout optimized for both desktop and mobile devices
  3. User-Friendly Features

    • Example Prompts: Five pre-written creative prompts covering various genres:
      • Cyberpunk cityscapes
      • Fantasy fairy scenes
      • Epic dragon imagery
      • Sci-fi space stations
      • Underwater ancient cities
    • Click-to-Use Examples: Simply click any example to instantly populate the prompt field
    • Advanced Settings: Collapsible panel for fine-tuning generation parameters
  4. Customizable Generation Parameters

    • Image Dimensions: Adjustable width and height (256-1152 pixels)
    • Inference Steps: Control speed vs. quality trade-off (6-25 steps)
    • Guidance Scale: Adjust prompt adherence (0.0-5.0)
    • Seed Control: Reproducible results with manual seed input

Technical Implementation

The application leverages cutting-edge technologies:

  • FLUX.1-dev: State-of-the-art diffusion model from Black Forest Labs
  • Hyper-SD LoRA: ByteDance's acceleration technology achieving 5-10x speedup
  • BFloat16 Precision: Reduced memory usage while maintaining quality
  • Gradio Spaces: GPU-accelerated deployment with automatic resource management
  • Custom CSS: Neon-themed styling with glow effects and animations

The generation pipeline:

  1. Loads the base FLUX.1-dev model in bfloat16 precision
  2. Applies Hyper-SD LoRA weights with 0.125 scaling factor
  3. Fuses LoRA weights for optimal performance
  4. Generates images using accelerated inference with custom parameters
  5. Outputs high-quality 1024x1024 images (default) in seconds

Performance Optimization

  • GPU Acceleration: Automatic CUDA optimization with @spaces.GPU decorator
  • Memory Efficiency: BFloat16 precision reduces VRAM usage by 50%
  • Inference Mode: Torch inference mode and autocast for maximum speed
  • TF32 Support: Enabled for compatible GPUs for additional speedup
  • Cached Models: Local model caching to reduce loading times

Use Cases

Perfect for:

  • Rapid prototyping of visual concepts
  • Creative exploration with instant feedback
  • Production of high-quality images for various projects
  • Testing different artistic styles and compositions
  • Educational purposes to understand AI image generation

ν•œκΈ€ μ„€λͺ…μ„œ

FLUX: Fast & Furious - μ΄ˆκ³ μ† 이미지 생성기

이 μ• ν”Œλ¦¬μΌ€μ΄μ…˜μ€ ByteDance의 AutoML νŒ€μ΄ κ°œλ°œν•œ Hyper-SD κΈ°μˆ μ„ ν™œμš©ν•˜μ—¬ FLUX.1-dev 이미지 생성 λͺ¨λΈμ„ κ°€μ†ν™”ν•œ λ²„μ „μœΌλ‘œ, κΈ°μ‘΄ 20-50단계가 ν•„μš”ν–ˆλ˜ 과정을 단 8λ‹¨κ³„λ‘œ 쀄여 κ³ ν’ˆμ§ˆ 이미지λ₯Ό μƒμ„±ν•©λ‹ˆλ‹€.

μ£Όμš” κΈ°λŠ₯

  1. μ΄ˆκ³ μ† 생성

    • ByteDance의 Hyper-SD LoRA(Low-Rank Adaptation) 기술 ν™œμš©
    • μΆ”λ‘  단계λ₯Ό 20-50λ‹¨κ³„μ—μ„œ 6-25λ‹¨κ³„λ‘œ λŒ€ν­ μΆ•μ†Œ (κΈ°λ³Έκ°’: 8단계)
    • 생성 μ‹œκ°„μ„ 획기적으둜 λ‹¨μΆ•ν•˜λ©΄μ„œλ„ 높은 이미지 ν’ˆμ§ˆ μœ μ§€
    • μ΅œλŒ€ μ„±λŠ₯을 μœ„ν•œ TF32 정밀도가 ν™œμ„±ν™”λœ CUDA μ΅œμ ν™”
  2. λ„€μ˜¨ ν…Œλ§ˆ μ‚¬μš©μž μΈν„°νŽ˜μ΄μŠ€

    • λ°œκ΄‘ λ„€μ˜¨ νš¨κ³Όκ°€ 적용된 μ‚¬μ΄λ²„νŽ‘ν¬ μŠ€νƒ€μΌμ˜ λ§žμΆ€ν˜• λ””μžμΈ
    • μ• λ‹ˆλ©”μ΄μ…˜ ν˜Έλ²„ νš¨κ³Όμ™€ 동적 μ‹œκ° ν”Όλ“œλ°±
    • νŒŒλž€μƒ‰, 청둝색, λ§ˆμ  νƒ€ 색상 μ•…μ„ΌνŠΈκ°€ μžˆλŠ” 닀크 ν…Œλ§ˆ
    • λ°μŠ€ν¬ν†±κ³Ό λͺ¨λ°”일 κΈ°κΈ° λͺ¨λ‘μ— μ΅œμ ν™”λœ λ°˜μ‘ν˜• λ ˆμ΄μ•„μ›ƒ
  3. μ‚¬μš©μž μΉœν™”μ  κΈ°λŠ₯

    • μ˜ˆμ‹œ ν”„λ‘¬ν”„νŠΈ: λ‹€μ–‘ν•œ μž₯λ₯΄λ₯Ό λ‹€λ£¨λŠ” 5개의 창의적인 ν”„λ‘¬ν”„νŠΈ 제곡:
      • μ‚¬μ΄λ²„νŽ‘ν¬ λ„μ‹œ 풍경
      • νŒνƒ€μ§€ μš”μ • μž₯λ©΄
      • μ›…μž₯ν•œ λ“œλž˜κ³€ 이미지
      • SF 우주 μ •κ±°μž₯
      • μˆ˜μ€‘ κ³ λŒ€ λ„μ‹œ
    • ν΄λ¦­ν•˜μ—¬ μ‚¬μš©: μ˜ˆμ‹œλ₯Ό ν΄λ¦­ν•˜λ©΄ μ¦‰μ‹œ ν”„λ‘¬ν”„νŠΈ ν•„λ“œμ— μž…λ ₯
    • κ³ κΈ‰ μ„€μ •: 생성 λ§€κ°œλ³€μˆ˜ λ―Έμ„Έ 쑰정을 μœ„ν•œ 접을 수 μžˆλŠ” νŒ¨λ„
  4. λ§žμΆ€ν˜• 생성 λ§€κ°œλ³€μˆ˜

    • 이미지 크기: μ‘°μ • κ°€λŠ₯ν•œ λ„ˆλΉ„μ™€ 높이 (256-1152 ν”½μ…€)
    • μΆ”λ‘  단계: 속도 λŒ€ ν’ˆμ§ˆ κ· ν˜• 쑰절 (6-25단계)
    • κ°€μ΄λ˜μŠ€ μŠ€μΌ€μΌ: ν”„λ‘¬ν”„νŠΈ μ€€μˆ˜λ„ μ‘°μ • (0.0-5.0)
    • μ‹œλ“œ μ œμ–΄: μˆ˜λ™ μ‹œλ“œ μž…λ ₯으둜 μž¬ν˜„ κ°€λŠ₯ν•œ κ²°κ³Ό

기술적 κ΅¬ν˜„

μ• ν”Œλ¦¬μΌ€μ΄μ…˜μ€ μ΅œμ²¨λ‹¨ κΈ°μˆ μ„ ν™œμš©ν•©λ‹ˆλ‹€:

  • FLUX.1-dev: Black Forest Labs의 μ΅œμ‹  ν™•μ‚° λͺ¨λΈ
  • Hyper-SD LoRA: 5-10λ°° 속도 ν–₯상을 λ‹¬μ„±ν•˜λŠ” ByteDance의 가속 기술
  • BFloat16 정밀도: ν’ˆμ§ˆμ„ μœ μ§€ν•˜λ©΄μ„œ λ©”λͺ¨λ¦¬ μ‚¬μš©λŸ‰ κ°μ†Œ
  • Gradio Spaces: μžλ™ λ¦¬μ†ŒμŠ€ 관리가 ν¬ν•¨λœ GPU 가속 배포
  • μ»€μŠ€ν…€ CSS: λ°œκ΄‘ νš¨κ³Όμ™€ μ• λ‹ˆλ©”μ΄μ…˜μ΄ μžˆλŠ” λ„€μ˜¨ ν…Œλ§ˆ μŠ€νƒ€μΌλ§

생성 νŒŒμ΄ν”„λΌμΈ:

  1. bfloat16 μ •λ°€λ„λ‘œ κΈ°λ³Έ FLUX.1-dev λͺ¨λΈ λ‘œλ“œ
  2. 0.125 μŠ€μΌ€μΌλ§ νŒ©ν„°λ‘œ Hyper-SD LoRA κ°€μ€‘μΉ˜ 적용
  3. 졜적 μ„±λŠ₯을 μœ„ν•œ LoRA κ°€μ€‘μΉ˜ μœ΅ν•©
  4. μ‚¬μš©μž μ •μ˜ λ§€κ°œλ³€μˆ˜λ‘œ κ°€μ†ν™”λœ 좔둠을 μ‚¬μš©ν•˜μ—¬ 이미지 생성
  5. λͺ‡ 초 λ§Œμ— κ³ ν’ˆμ§ˆ 1024x1024 이미지(κΈ°λ³Έκ°’) 좜λ ₯

μ„±λŠ₯ μ΅œμ ν™”

  • GPU 가속: @spaces.GPU λ°μ½”λ ˆμ΄ν„°λ‘œ μžλ™ CUDA μ΅œμ ν™”
  • λ©”λͺ¨λ¦¬ νš¨μœ¨μ„±: BFloat16 μ •λ°€λ„λ‘œ VRAM μ‚¬μš©λŸ‰ 50% κ°μ†Œ
  • μΆ”λ‘  λͺ¨λ“œ: μ΅œλŒ€ 속도λ₯Ό μœ„ν•œ Torch μΆ”λ‘  λͺ¨λ“œμ™€ μžλ™ 캐슀트
  • TF32 지원: ν˜Έν™˜ GPUμ—μ„œ μΆ”κ°€ 속도 ν–₯상을 μœ„ν•΄ ν™œμ„±ν™”
  • μΊμ‹œλœ λͺ¨λΈ: λ‘œλ”© μ‹œκ°„ 단좕을 μœ„ν•œ 둜컬 λͺ¨λΈ 캐싱

μ‚¬μš© 사둀

λ‹€μŒκ³Ό 같은 μš©λ„μ— μ ν•©ν•©λ‹ˆλ‹€:

  • μ‹œκ°μ  μ»¨μ…‰μ˜ μ‹ μ†ν•œ ν”„λ‘œν† νƒ€μ΄ν•‘
  • 즉각적인 ν”Όλ“œλ°±μœΌλ‘œ 창의적 탐색
  • λ‹€μ–‘ν•œ ν”„λ‘œμ νŠΈλ₯Ό μœ„ν•œ κ³ ν’ˆμ§ˆ 이미지 μ œμž‘
  • λ‹€μ–‘ν•œ 예술적 μŠ€νƒ€μΌκ³Ό ꡬ성 ν…ŒμŠ€νŠΈ
  • AI 이미지 생성 이해λ₯Ό μœ„ν•œ ꡐ윑 λͺ©μ 