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- ---
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- license: apache-2.0
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- ---
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- # Kurai Toori Dark Streets - Quantized Model
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-
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- This repository contains a quantized model used to synthetically generate the [Kurai Toori Dark Streets dataset](https://huggingface.co/datasets/takara-ai/kurai_toori_dark_streets). The model is optimized for use with [stable-diffusion.cpp](https://github.com/leejet/stable-diffusion.cpp) for efficient running on lower-end hardware.
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-
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- ## Model Details
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-
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- - **Format**: GGUF (GPT-Generated Unified Format)
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- - **Use Case**: Generating high-quality images with lower hardware requirements
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- - **Compatibility**: Designed for use with stable-diffusion.cpp
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-
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- ## Key Features
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-
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- - Optimized for lower-end hardware
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- - Capable of producing high-quality images
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- - Specifically used to generate the Kurai Toori Dark Streets dataset
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- - Efficient performance due to quantization
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-
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- ## Usage
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-
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- To use this model with stable-diffusion.cpp:
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-
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- 1. Clone the stable-diffusion.cpp repository:
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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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- ```
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-
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- 2. Follow the setup instructions in the stable-diffusion.cpp README.
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- 3. Download the GGUF model file from this repository.
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- 4. Run the model using the stable-diffusion.cpp interface, pointing to the downloaded GGUF file.
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- ## Dataset Generation
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- This model was used to create the Kurai Toori Dark Streets dataset, which features synthetically generated high-quality images. While the dataset focuses on dark and atmospheric street scenes, the model itself is capable of generating a wide range of high-quality images. The dataset can be found [here](https://huggingface.co/datasets/takara-ai/kurai_toori_dark_streets).
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-
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- ## Performance
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- Due to its quantized nature, this model offers:
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- - Reduced memory usage
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- - Faster inference times
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- - Ability to run on less powerful hardware without significant quality loss
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-
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- ## License
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- This model is released under the Apache 2.0 license. Please see the LICENSE file for more details.
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-
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- ## Acknowledgements
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-
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- - Thanks to the creators of stable-diffusion.cpp for providing an efficient C++ implementation of Stable Diffusion.
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- - Credit to the Hugging Face community for hosting the dataset and fostering open-source AI development.
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- For any questions or issues, please open an issue in this repository.
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-
 
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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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+ # Flux.1 Q_4_k
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+
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+ This repository contains a quantized GGUF model optimized for [stable-diffusion.cpp](https://github.com/leejet/stable-diffusion.cpp), enabling efficient image generation on lower-end hardware. It 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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+
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+ - Optimized for lower-end hardware
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+ - High-quality image generation
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+ - Efficient performance through quantization
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+ - Wide-ranging capabilities beyond dark street scenes
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+
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+ ## Usage
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+
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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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+ ## Performance Benefits
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+
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+ - Reduced memory usage
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+ - Faster inference times
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+ - Runs on less powerful hardware without significant quality loss
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+
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+ ## License
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+
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+ Apache 2.0 (see LICENSE file for details)
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+
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+ ## Acknowledgements
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+ - [stable-diffusion.cpp](https://github.com/leejet/stable-diffusion.cpp) creators
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+ - [Hugging Face](https://huggingface.co/) community
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+
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+ For questions or issues, please open an issue in this repository.