| --- |
| license: creativeml-openrail-m |
| language: |
| - en |
| pipeline_tag: text-to-image |
| --- |
| |
| # 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 or at [fal.ai](https://fal.ai/models/fal-ai/f-lite/standard). |
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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/fal-ai/f-lite). |
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| # Technical Report |
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| Read the [technical report](https://github.com/fal-ai/f-lite/blob/main/assets/F%20Lite%20Technical%20Report.pdf) to learn more about the model details. |
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| # Limitations and Bias |
| * The models can generate malformations. |
| * The text capabilities of the model are limited. |
| * 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 |
| * Use long prompts to generate better results. Short prompts may result in low-quality images. |
| * 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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|
| ``` |
| @article{ryu2025flite, |
| title={F Lite Technical Report}, |
| author={Ryu, Simo and Pengqi, Lu and Mart\'in Juan, Javier and de Prado Alonso, Iv\'an}, |
| year={2025} |
| } |
| ``` |
