Model Card v1
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README.md
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# F-Lite Model Card
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F-Lite is a 10B parameter diffusion model created by [Freepik](https://www.freepik.com) and [Fal](https://fal.ai), trained exclusively on copyright-safe and SFW content. The model was trained on Freepik's internal dataset comprising approximately 80 million copyright-safe images, making it the first publicly available model of this scale trained exclusively on legally compliant and SFW content.
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## Usage
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Experience F-Lite instantly through our [interactive demo](https://huggingface.co/spaces/Freepik/F-Lite) on Hugging Face.
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F-Lite works with both the `diffusers` library and [ComfyUI](https://www.comfy.org/). For details, see the [F-Lite GitHub repository](https://github.com/Freepik/F-Lite).
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# Technical Report
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Read the [technical report](XXXXX) to learn more about the model details.
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# Limitations and Bias
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* The models can generate malformations.
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* The text capabilities of the model are limited.
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* The model can be subject to biases, although we think we have a good balance given the quality and variety of the Freepik's dataset.
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# Recommendations
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* Use long prompts to generate better results. Short prompts may result in low-quality images.
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* Generate images above the megapixel. Smaller images will result in low-quality images.
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## Acknowledgements
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This model uses [T5 XXL](https://huggingface.co/google/t5-v1_1-xxl)and [Flux Schnell VAE](https://huggingface.co/black-forest-labs/FLUX.1-schnell)
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## License
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The F-Lite weights are licensed under the permissive CreativeML Open RAIL-M license. The T5 XXL and Flux Schnell VAE are licensed under Apache 2.0.
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## Citation
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If you find our work helpful, please cite it!
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```
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@article{ryu2025flite,
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title={F-Lite Technical Report},
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author={Ryu, Simo and Pengqi, Lu and Mart\'in Juan, Javier and de Prado Alonso, Iv\'an},
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year={2025}
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}
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```
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output_tight_mosaic.jpeg
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Git LFS Details
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