https://github.com/litaotju/freeflux
Smart and Simple Flux for GPU-poor
https://github.com/litaotju/freeflux
ai deepseek deepseek-ai deepseek-r1 flux prompt-engineering stable-diffusion stable-diffusion-webui text-to-image text-to-image-ai text-to-image-diffusion text-to-image-generation
Last synced: 3 months ago
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Smart and Simple Flux for GPU-poor
- Host: GitHub
- URL: https://github.com/litaotju/freeflux
- Owner: litaotju
- License: mit
- Created: 2025-02-28T18:41:51.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2025-02-28T18:54:57.000Z (3 months ago)
- Last Synced: 2025-02-28T22:38:51.426Z (3 months ago)
- Topics: ai, deepseek, deepseek-ai, deepseek-r1, flux, prompt-engineering, stable-diffusion, stable-diffusion-webui, text-to-image, text-to-image-ai, text-to-image-diffusion, text-to-image-generation
- Language: Python
- Homepage: https://github.com/litaotju/freeflux
- Size: 392 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# FreeFlux: Smart and Simple Flux for GPU-poor
Make FLUX more accessible to the public using 4-bit quantized model, and using CPU offloading technique, allowing a 12GB GPU to run FLUX.
Be able to use **DeepSeek-R1 AI** to generate fantistic prompts for FLUX from really simple keywords, which is a quality of life improvement, since I never get the tips and tricks to generate good prompts. **Note: to use this you need an OpenAI API Compitable endpoint and your API key, Aliyun is a very good candidate!!**
Tested on NVIDIA Geforce RTX 3060 12GB, with Ubuntu 22.04 Linux, Python 3.10.12, 64GB CPU memory. AMD GPUs are not supported.
## Features:
- [x] 4-bit Flux-DEV quantized model
- [x] Optional CPU offloading
- [x] DeepSeek-R1 AI prompt generation
- [x] LoRA and multiple LoRAs
- [x] Gallery browse and management
- [x] One-click install
- [x] Gradio UI
- [x] CLI command for batch generation
## Install
```bash
git clone https://github.com/litaotju/freeflux
cd freeflux
# recommended to use virtualenv to avoid polluting the system python environment
python -m venv .venv && source .venv/bin/activate
pip install -e ./
```
## Usage
Start an gradio app in the local server, and use the UI.
```bash
python -m freeflux.app
```
Thats it, enjoy the images!!
The UI will look like this:
## Dependencies:
Tested torch 2.4.0, diffuser 0.30.3, bitsandbytes 0.45.2, transformers 4.49.0, gradio 5.17.1
Other versions may work, but not tested.
## Common Issues
1. This app will need to connect the Huggingface and download models, use a proxy if you are China.
## Acknowledgement
Inspired by and utilizing the models provided by the following repo
- https://huggingface.co/HighCWu/FLUX.1-dev-4bit
- https://github.com/HighCWu/flux-4bit
- https://huggingface.co/PrunaAI/FLUX.1-schnell-4bit