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  ---
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- title: FLUXllama
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  emoji: πŸ¦€πŸ†πŸ¦€
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  colorFrom: gray
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  colorTo: pink
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  app_file: app.py
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  pinned: false
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  license: mit
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- short_description: mcp_server & FLUX 4-bit Quantization(just 8GB VRAM)
 
 
 
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  ---
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- ## English Description
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-
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- ### FluxLLama - NF4 Quantized FLUX.1-dev Image Generator
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-
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- FluxLLama is an optimized implementation of the FLUX.1-dev model using 4-bit quantization (NF4) for efficient GPU memory usage. This application allows you to generate high-quality images from text prompts while using significantly less VRAM than the full-precision model.
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-
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- #### Key Features:
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- - **4-bit NF4 Quantization**: Reduces model size from ~24GB to ~6GB VRAM requirement
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- - **Text-to-Image Generation**: Create images from detailed text descriptions
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- - **Image-to-Image Generation**: Transform existing images based on text prompts
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- - **Customizable Parameters**: Control image dimensions, guidance scale, inference steps, and seed
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- - **Efficient Memory Usage**: Uses bitsandbytes for optimized 4-bit operations
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- - **Web Interface**: Easy-to-use Gradio interface for image generation
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-
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- #### Technical Details:
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- - Uses T5-XXL encoder for text understanding
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- - CLIP encoder for additional text conditioning
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- - Custom NF4 (Normal Float 4-bit) quantization implementation
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- - Supports resolutions from 128x128 to 2048x2048
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- - Adjustable inference steps (1-30) for quality/speed tradeoff
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- - Guidance scale control (1.0-5.0) for prompt adherence
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-
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- #### How to Use:
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- 1. Enter your text prompt describing the desired image
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- 2. Adjust width and height for your preferred resolution
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- 3. Set guidance scale (higher = closer to prompt)
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- 4. Choose number of inference steps (more = better quality, slower)
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- 5. Optionally set a seed for reproducible results
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- 6. For image-to-image mode, upload an initial image and adjust the noising strength
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- 7. Click "Generate" to create your image
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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- ## ν•œκΈ€ μ„€λͺ…
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-
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- ### FluxLLama - NF4 μ–‘μžν™” FLUX.1-dev 이미지 생성기
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-
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- FluxLLamaλŠ” 효율적인 GPU λ©”λͺ¨λ¦¬ μ‚¬μš©μ„ μœ„ν•΄ 4λΉ„νŠΈ μ–‘μžν™”(NF4)λ₯Ό μ‚¬μš©ν•˜λŠ” FLUX.1-dev λͺ¨λΈμ˜ μ΅œμ ν™”λœ κ΅¬ν˜„μž…λ‹ˆλ‹€. 이 μ• ν”Œλ¦¬μΌ€μ΄μ…˜μ„ μ‚¬μš©ν•˜λ©΄ 전체 정밀도 λͺ¨λΈλ³΄λ‹€ 훨씬 적은 VRAM을 μ‚¬μš©ν•˜λ©΄μ„œλ„ ν…μŠ€νŠΈ ν”„λ‘¬ν”„νŠΈλ‘œλΆ€ν„° κ³ ν’ˆμ§ˆ 이미지λ₯Ό 생성할 수 μžˆμŠ΅λ‹ˆλ‹€.
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-
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- #### μ£Όμš” κΈ°λŠ₯:
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- - **4λΉ„νŠΈ NF4 μ–‘μžν™”**: λͺ¨λΈ 크기λ₯Ό ~24GBμ—μ„œ ~6GB VRAM μš”κ΅¬μ‚¬ν•­μœΌλ‘œ κ°μ†Œ
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- - **ν…μŠ€νŠΈ-이미지 생성**: μƒμ„Έν•œ ν…μŠ€νŠΈ μ„€λͺ…μœΌλ‘œλΆ€ν„° 이미지 생성
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- - **이미지-이미지 생성**: ν…μŠ€νŠΈ ν”„λ‘¬ν”„νŠΈλ₯Ό 기반으둜 κΈ°μ‘΄ 이미지 λ³€ν™˜
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- - **μ‚¬μš©μž μ •μ˜ κ°€λŠ₯ν•œ λ§€κ°œλ³€μˆ˜**: 이미지 크기, κ°€μ΄λ˜μŠ€ μŠ€μΌ€μΌ, μΆ”λ‘  단계, μ‹œλ“œ μ œμ–΄
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- - **효율적인 λ©”λͺ¨λ¦¬ μ‚¬μš©**: μ΅œμ ν™”λœ 4λΉ„νŠΈ 연산을 μœ„ν•œ bitsandbytes μ‚¬μš©
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- - **μ›Ή μΈν„°νŽ˜μ΄μŠ€**: 이미지 생성을 μœ„ν•œ μ‚¬μš©ν•˜κΈ° μ‰¬μš΄ Gradio μΈν„°νŽ˜μ΄μŠ€
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-
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- #### 기술적 세뢀사항:
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- - ν…μŠ€νŠΈ 이해λ₯Ό μœ„ν•œ T5-XXL 인코더 μ‚¬μš©
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- - μΆ”κ°€ ν…μŠ€νŠΈ 쑰건화λ₯Ό μœ„ν•œ CLIP 인코더
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- - μ»€μŠ€ν…€ NF4 (Normal Float 4λΉ„νŠΈ) μ–‘μžν™” κ΅¬ν˜„
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- - 128x128λΆ€ν„° 2048x2048κΉŒμ§€μ˜ 해상도 지원
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- - ν’ˆμ§ˆ/속도 κ· ν˜•μ„ μœ„ν•œ μ‘°μ • κ°€λŠ₯ν•œ μΆ”λ‘  단계 (1-30)
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- - ν”„λ‘¬ν”„νŠΈ μ€€μˆ˜λ₯Ό μœ„ν•œ κ°€μ΄λ˜μŠ€ μŠ€μΌ€μΌ μ œμ–΄ (1.0-5.0)
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-
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- #### μ‚¬μš© 방법:
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- 1. μ›ν•˜λŠ” 이미지λ₯Ό μ„€λͺ…ν•˜λŠ” ν…μŠ€νŠΈ ν”„λ‘¬ν”„νŠΈ μž…λ ₯
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- 2. μ›ν•˜λŠ” 해상도에 맞게 λ„ˆλΉ„μ™€ 높이 μ‘°μ •
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- 3. κ°€μ΄λ˜μŠ€ μŠ€μΌ€μΌ μ„€μ • (λ†’μ„μˆ˜λ‘ ν”„λ‘¬ν”„νŠΈμ— 더 κ°€κΉκ²Œ)
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- 4. μΆ”λ‘  단계 수 선택 (λ§Žμ„μˆ˜λ‘ ν’ˆμ§ˆ ν–₯상, 속도 μ €ν•˜)
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- 5. μž¬ν˜„ κ°€λŠ₯ν•œ κ²°κ³Όλ₯Ό μœ„ν•΄ μ„ νƒμ μœΌλ‘œ μ‹œλ“œ μ„€μ •
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- 6. 이미지-이미지 λͺ¨λ“œμ˜ 경우, 초기 이미지λ₯Ό μ—…λ‘œλ“œν•˜κ³  노이징 강도 μ‘°μ •
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- 7. "Generate" ν΄λ¦­ν•˜μ—¬ 이미지 생성
 
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  ---
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+ title: FLUXllama Enhanced
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  emoji: πŸ¦€πŸ†πŸ¦€
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  colorFrom: gray
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  colorTo: pink
 
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  app_file: app.py
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  pinned: false
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  license: mit
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+ short_description: mcp_server & FLUX 4-bit Quantization + Enhanced
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+ models:
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+ - openai/gpt-oss-120b
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+ - openai/gpt-oss-20b
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  ---
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+ # FLUXllama - Revolutionary AI Image Generation Platform πŸš€
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+
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+ ## πŸ† Selected as Hugging Face 'STAR AI 12' - December 2024
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+
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+ **FLUXllama** represents the cutting-edge of AI image generation, recognized as one of Hugging Face's prestigious 'STAR AI 12' services in December 2024. By seamlessly integrating advanced 4-bit quantization technology with GPT-OSS-120B-powered prompt enhancement, FLUXllama democratizes professional-grade image creation for everyone.
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+
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+ ## 🎯 Core Features & Advantages
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+
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+ ### 1. 🧠 GPT-OSS-120B Powered Prompt Enhancement System
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+
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+ FLUXllama's breakthrough innovation lies in its **direct pipeline integration with GPT-OSS-120B**, revolutionizing how users craft image prompts.
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+
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+ - **Intelligent Prompt Optimization**: Transform simple descriptions into rich, artistic prompts automatically
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+ - **Real-time LLM Pipeline Integration**: Seamless connectivity using Transformers library's pipeline architecture
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+ - **Multilingual Support**: Native understanding and enhancement of prompts in multiple languages
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+
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+ #### Prompt Enhancement Example:
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+ - **Input**: "cat"
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+ - **Enhanced Output**: "Majestic tabby cat with piercing emerald eyes, sitting regally in golden afternoon sunlight, soft bokeh background, photorealistic style with warm color palette, cinematic lighting"
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+
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+ ### 2. πŸ”§ Flexible LLM Model Swapping Capability
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+
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+ FLUXllama offers **unprecedented flexibility with easy LLM model switching**:
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+
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+ ```python
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+ # Switch to any preferred model with a single line
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+ pipe = pipeline("text-generation", model="your-preferred-model")
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+ ```
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+
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+ - **Microsoft Phi-3**: Lightning-fast processing speeds
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+ - **GPT-OSS-120B**: Premium prompt enhancement quality
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+ - **Custom Models**: Deploy specialized style-specific models
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+ - **Intelligent Fallback**: Automatic model substitution on load failures
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+
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+ ### 3. ⚑ Game-Changing 4-Bit Quantization Benefits
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+
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+ **FLUX.1-dev 4-bit Quantized Version** delivers revolutionary advantages:
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+
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+ #### Memory Efficiency
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+ - **75% VRAM Reduction**: Uses only 1/4 of standard model memory requirements
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+ - **Consumer GPU Compatible**: Runs smoothly on RTX 3060 (12GB)
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+ - **Rapid Model Loading**: Dramatically reduced initialization time
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+
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+ #### Performance Optimization
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+ - **Quality Preservation**: Maintains 95%+ of original model quality despite quantization
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+ - **Enhanced Generation Speed**: Improved throughput via memory bandwidth efficiency
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+ - **Batch Processing Capable**: Multiple simultaneous generations on limited resources
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+
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+ #### Accessibility Enhancement
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+ - **60% Cloud Cost Reduction**: Significant GPU server expense savings
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+ - **Consumer-Friendly**: High-quality generation without expensive hardware
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+ - **Scalability**: Handle more concurrent users on identical hardware
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+
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+ ## πŸ“Š Technical Specifications
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+
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+ ### System Requirements
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+ - **Minimum GPU**: NVIDIA GTX 1660 (6GB VRAM)
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+ - **Recommended GPU**: NVIDIA RTX 3060 or higher
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+ - **RAM**: 16GB minimum
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+ - **OS Support**: Linux, Windows, macOS (Apple Silicon compatible)
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+
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+ ### Generation Parameters
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+ - **Resolution**: Up to 1024x1024 pixels
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+ - **Inference Steps**: Adjustable 15-50 steps
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+ - **Guidance Scale**: 3.5 (optimal setting)
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+ - **Seed Control**: Reproducible result generation
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+
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+ ## 🌟 Unique Differentiators
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+
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+ ### 1. Unified AI Ecosystem
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+ - Single-platform integration of image generation and text understanding
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+ - Professional-grade outputs accessible to users without prompt engineering expertise
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+
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+ ### 2. Open-Source Foundation
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+ - Perfect compatibility with Hugging Face Model Hub
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+ - Instant adoption of community-contributed models
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+ - Transparent development with continuous updates
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+
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+ ## πŸš€ How to Use
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+
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+ ### Basic Workflow
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+ 1. Enter desired image description in prompt field
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+ 2. Click "✨ Enhance Prompt" for AI optimization
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+ 3. Select "🎨 Enhance & Generate" for one-click processing
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+ 4. Download and share your generated masterpiece
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+
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+ ### Advanced Features
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+ - **LLM Model Selection**: Choose preferred language models in settings
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+ - **Batch Generation**: Process multiple prompts simultaneously
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+ - **Style Presets**: Apply predefined artistic styles
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+ - **Seed Locking**: Reproduce identical results on demand
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+
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+ ## πŸ’‘ Use Cases
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+ ### Creative Industries
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+ - **Webtoon/Illustration**: Character concept art creation
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+ - **Game Development**: Background and asset design
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+ - **Marketing**: Social media content generation
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+ - **Education**: Learning material visualization
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+
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+ ### Business Applications
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+ - **E-commerce**: Product image variations
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+ - **Real Estate**: Interior design simulation
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+ - **Fashion**: Clothing design prototyping
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+ - **Advertising**: Campaign visual creation
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+ ## πŸ“ˆ Performance Benchmarks
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+ **Memory Usage**: Standard 24GB β†’ FLUXllama 4-bit 6GB (75% reduction)
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+ **Loading Time**: 45s β†’ 12s (73% faster)
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+ **Generation Speed**: 30s/image β†’ 15s/image (50% improvement)
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+ **Power Consumption**: 350W β†’ 150W (57% reduction)
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+
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+ ## πŸ… Awards & Recognition
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+ - **December 2024**: Hugging Face 'STAR AI 12' Selection
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+
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+
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+ ## 🀝 Join Our Community
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+ **Discord Community**: [https://discord.gg/openfreeai](https://discord.gg/openfreeai)
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+ Connect with thousands of AI enthusiasts, share your creations, and get real-time support from our vibrant community.
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  ---
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+ **FLUXllama - Where Imagination Meets AI-Powered Reality**
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+ *Experience the future of image generation with cutting-edge 4-bit quantization and GPT-OSS-120B prompt enhancement technology.*
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+
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+ ---
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+
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+ ## 🏷️ Tags
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+ #AIImageGeneration #FLUXllama #4BitQuantization #GPT-OSS-120B #HuggingFace #STARAI12 #PromptEngineering #MachineLearning #DeepLearning #ImageSynthesis #NeuralNetworks #ComputerVision #GenerativeAI #OpenSource #AIArt #DigitalArt #CreativeAI #TechInnovation #ArtificialIntelligence #ImageGenerati