Aesthetic Amateur Photo

    Aesthetic_Amateur_Photo_V3.safetensors LORA / Flux.1 D

    Model Information
    Model Name
    Aesthetic Amateur Photo
    Version
    V3
    Creator
    powerpuff
    Size
    18.64 MB
    Downloads
    2,092
    Torrent Details
    BTIH
    DCD7302D6D56A71F2B6CBE14D3D4491D38FD09F9
    BTMH
    F402311F93A61D5315266CDAC8B87C951035606E649B0C662F6F3A1643C06C08
    SHA256
    466BCAA588F73E21FADB17BAB086318B462A42D0253E9309AD04EDE47E604BB2
    Upload Date
    about a year ago
    Uploader
    CivitasBay.org
    Status
    Not currently seeded — request it
    0 Seeders
    0 Peers
    Info

    Another amateur photo LoRA aimed at making images feel more realistic and closer to everyday smartphone or social media photos. Expect sharper details, brighter colors, and a more casual, natural look overall.


    Krea V4:

    Higher quality dataset, more steps, better captions.

    Krea V3:

    Similar to V2 but the captions used a tag-style instead of full sentences.

    Krea V2:

    More steps, more images, completely new captions

    Krea V1:

    Initial release trained with basic captions.


    Z-Image Exp 1:

    Experimental version trained with chinese captions.

    Only 2000 steps and a small dataset but produces pretty good images.

    Trigger:

    这张照片是用iPhone 13拍摄的。

    Z-Image V2:

    More than doubled the steps compared to V1

    Stronger effect

    Can be used with higher strength

    Z-Image V1:

    A new version for Z-Image trained on a small dataset.


    V4 Beta 2:

    Trained on more images.

    V4 Beta 1:

    I have started to create a completely new dataset with only high quality images. For Beta 1 I used 111 images, though I plan to significantly increase it for Beta 2. All images only have the caption "43stet1c", but it isn't needed to mention it in your prompt.

    This combination seems to produce the best and most consistent results so far.

    Increase the strength if the effect isn't strong enough.

    V3:

    Same dataset as V2 but completely recaptioned with Claude 3.5 Sonnet and upscaled to 1024 with Gigapixel.

    V2:

    Trained on 124 images with no captions at all. Let me know if this works better than V1. Results can be inconsistent, use HiRes fix and Beta scheduler.

    V1:

    This was trained on a dataset of 61 "aesthetic" images captioned with Claude 3.5 Sonnet.

    Gallery
    This model contains NSFW content. Click to show gallery.
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