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  # Flux.1 Lite
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- We are excited to announce the alpha version of our new distilled Flux.1 Lite model, an 8B parameter transformer model distilled from the original Flux1. dev model.
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- Our goal is to further reduce FLUX.1-dev transformer parameters to approximately 24 GB to make it compatible with most of GPU cards.
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  ![Flux.1 Lite vs FLUX.1-dev](./sample_images/models_comparison.png)
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  ## Motivation
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- As stated by other members of the community like [Ostris](https://ostris.com/2024/09/07/skipping-flux-1-dev-blocks/), it seems that each of the blocks of the Flux1.dev transformer is not contributing equally to the final image generation. To confirm this hypothesis, we can measure the Mean Squared Error (MSE) between the input and the output of each block. As we can see in the following images, the mse differs a lot between the different blocks.
 
 
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  ![Flux.1 Lite generated image](./sample_images/skip_blocks/generated_img.png)
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  ![MSE MMDIT](./sample_images/skip_blocks/mse_mmdit_img.png)
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  ## Text-to-Image Usage
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- It is recommended to use a `guidance_scale` of 3.5 and a `n_steps` between 22 and 30 for best results.
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  ```python
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  import torch
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  ```
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  ## ComfyUI
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- We also provided a ComfyUI workflow in `comfy/flux.1-lite_workflow.json`
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  ![ComfyUI workflow](./comfy/flux.1-lite_workflow.png)
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  ## Checkpoints
 
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  # Flux.1 Lite
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+ We are thrilled to announce the alpha release of Flux.1 Lite, an 8B parameter transformer model distilled from the FLUX.1-dev model.
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+ Our goal? To distill FLUX.1-dev into a lighter model, reducing the parameters to just 24 GB, so it can run smoothly on most consumer-grade GPU cards, making high-quality AI models accessible to everyone.
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  ![Flux.1 Lite vs FLUX.1-dev](./sample_images/models_comparison.png)
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  ## Motivation
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+ As stated by other members of the community like [Ostris](https://ostris.com/2024/09/07/skipping-flux-1-dev-blocks/), it seems that blocks of the Flux1.dev transformer have a different contribution to the final image generation. To explore this, we analyzed the Mean Squared Error (MSE) between the input and output of each block, revealing significant variability.
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+ Our findings? Not all blocks are created equal. By strategically skipping less impactful blocks, we've managed to achieve incredible efficiency gains without compromising on quality. The results are striking: skipping just one of the early MMDIT blocks can significantly impact model performance, whereas other blocks have a much smaller effect.
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  ![Flux.1 Lite generated image](./sample_images/skip_blocks/generated_img.png)
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  ![MSE MMDIT](./sample_images/skip_blocks/mse_mmdit_img.png)
 
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  ## Text-to-Image Usage
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+ Flux.1 Lite is ready to unleash your creativity! For the best results, we recommend using a `guidance_scale` of 3.5 and setting `n_steps` between 22 and 30.
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  ```python
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  import torch
 
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  ```
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  ## ComfyUI
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+ We've also crafted a ComfyUI workflow to make using Flux.1 Lite even more seamless! Find it in `comfy/flux.1-lite_workflow.json`.
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  ![ComfyUI workflow](./comfy/flux.1-lite_workflow.png)
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  ## Checkpoints