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    EBE - imagine diffusion - sd1.5-alpha
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    EBE - imagine diffusion

    EBE (Enhanced By Ehristoforu) is a modern project whose task is to create the best universal and balanced diffusion models based on SD1.5, SD2.1, SDXL, PonyV6, SD3 and others.

    About this project

    Who is working on the project

    The Project Fluently and DreamDrop team led by ehristoforu are working on this project.

    What are the goals of the project

    Our project has several key goals:

    • Creating the most versatile and balanced models

    • Creating a friendly community in Discord/HuggingFace, where everyone will participate in improving the models

    • Creation of LoRAs for different tasks

    • Creating styles for our models

    Current roadmap

    Our roadmap looks like this:

    1. Creation of EBE based on SD1.5

    2. Creation of EBE based on SD2.1

    3. Creation of EBE based on SDXL

    4. Creation of EBE based on PonyV6

    5. Creation of EBE based on SD3 Medium

    6. Creation of LoRAS for EBE based on SD1.5

    7. Creation of LoRAS for EBE based on SDXL

    8. Creation of LoRAS for EBE based on PonyV6

    9. Creation of LoRAS for EBE based on SD3 Medium

    10. Create a large number of quality styles for EBE models

    How our models are created

    We use several techniques at once:

    • Training base models on large datasets

    • Megring well-selected models

    • We train LoRAs and integrate them into based models

    Is merging harmful to the model?

    In our case no, we carefully select and test models for merge, run tests using X/Y/Z plot and much more, so don't worry.

    Links to our resources:

    • Our LoRAs: coming soon

    • Our styles: coming soon

    • HuggingFace: here

    • Our site: coming soon

    • Our Discord community: coming soon

    Thanks 💖

    Description

    Work done:

    • The model was trained on a large dataset.

    • More than 20 best models took part in the merger

    Results:

    • Improved overall aesthetics and quality

    • Improved understanding and adherence to prompts

    • Improved tokens: cinematic, depth of field, semi-realistic