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--- |
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license: apache-2.0 |
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base_model: |
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- black-forest-labs/FLUX.1-schnell |
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pipeline_tag: text-to-image |
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--- |
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<img src="https://takara.ai/images/logo-24/TakaraAi.svg" width="200" alt="Takara.ai Logo" /> |
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From the Frontier Research Team at **Takara.ai** we present **Flux.1 Q_4_k**, a quantized GGUF model optimized for [stable-diffusion.cpp](https://github.com/leejet/stable-diffusion.cpp), enabling efficient image generation on lower-end hardware. This model was used to create the [Kurai Toori Dark Streets dataset](https://huggingface.co/datasets/takara-ai/kurai_toori_dark_streets). |
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--- |
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## Features |
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- Optimized for lower-end hardware through 4-bit quantization |
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- High-quality image generation despite compression |
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- Efficient performance with minimal quality degradation |
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- Wide-ranging capabilities beyond dark street scenes |
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## Usage |
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1. Clone and set up stable-diffusion.cpp: |
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``` |
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git clone https://github.com/leejet/stable-diffusion.cpp.git |
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cd stable-diffusion.cpp |
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# Follow setup instructions in the stable-diffusion.cpp README |
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``` |
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2. Download the GGUF model file from this repository. |
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3. Run the model using stable-diffusion.cpp, pointing to the downloaded file: |
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``` |
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./sd -m path/to/flux.1-q_4_k.gguf -p "your prompt here" |
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``` |
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## Performance Benefits |
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- Reduced memory usage compared to full-precision models |
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- Faster inference times on consumer hardware |
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- Runs on less powerful hardware without significant quality loss |
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- Ideal for experimentation and rapid prototyping |
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## Technical Details |
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This model is a 4-bit quantized version of the FLUX.1-schnell base model from Black Forest Labs. The quantization process preserves the creative capabilities of the original model while dramatically reducing its memory footprint and computational requirements. |
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## Example Use Cases |
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- Generating urban nightscapes and cityscapes |
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- Creating artistic interpretations for creative projects |
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- Rapid prototyping of visual concepts |
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- Accessible AI image generation on consumer hardware |
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--- |
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For research inquiries and press, please reach out to research@takara.ai |
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> 人類を変革する |
