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    HUNYUAN v1.0 (Olsen in 2012) :

    Trained on Hunyuan Video fp8 with 512x512 px with 58 photos of Elizabeth Olsen in 2012 with detailed GPT-4 captions. Tested on Hunyuan Video fp8 and Fast Hunyuan Video fp8 ! No keywords needed. Use around Lora strength=1.1.embedded_guidance_scale= 5.0-8.0 and flow_shift=7.0-12.0:

    Positive : {Short summary of the scene e.g. Professional video of a blonde woman giving and interview on the red carpet}, {more detailed scene and background description}, {lighting description}, {camera direction e.g. panning in, panning out, zoom in etc.},<lora:eliolsen_2012_hunyuan_epoch60:1.1>

    FLUX v.2 (Olsen in 2017) :

    Please Donate Buzz for FLUX Lora Training !

    Trained on FLUX.1 [dev] with 80 photos of Elizabeth Olsen in 2017 with detailed GPT-4 captions. Tested on FLUX 1.dev (full) and FLUX fp8 and FLUX nf4 ! No keywords needed. Use around strength 0.8-1.0. Distilled CFG 3.5 and CFG 1.0 (without negative prompt). Clipskip 1. Can be used for example as follows:

    Positive : {Artstyle, Character and scene description in usual FLUX fashion}, <lora:eliolsen_2017_local_164_merger_20v1_8v2_34v2_03_03_04:1>

    FLUX v.1 (Olsen in 2012) :

    Trained on FLUX.1 [dev] with 70 photos of Elizabeth Olsen in 2012 with detailed GPT-4 captions. Tested on FLUX 1.dev (full) and FLUX fp8 and FLUX nf4 ! Use around strength 0.8-1.0. Distilled CFG 3.5 and CFG 1.0 (without negative prompt). Clipskip 1. Can be used for example as follows:

    Positive : {Artstyle, Character and scene description in usual FLUX fashion}, <lora:Elizabeth_Olsen_2012_FLUX_epoch_46:1>

    SDXL v8.0 2012:

    Last versions probably. I wasn't satisfied with the likeness of the other models so I restricted all images to around 2012. Trained on Juggernaut X with 220 photos of Elizabeth Olsen in 2012. Tested on Juggernaut X, Juggernaut v7, RealismEngine 2, RealVisXL3 and AlbedoBase 2.0! Use with keyword : "elxolsn" . Use around strength 1.0-1.1. CFG 5.0-7.0. Clipskip 1. 10-40 steps. Can be used for example as follows:

    Positive : {Artstyle}, {Character and scene description}, elxolsn, <lora:eliolsen_2012_juggerX_xl_1_wocap-elxolsn-000120:1.05>

    Negative : ugly, deformed, airbrushed, photoshop, rendered, (multiple people), child

    SDXL v7.0 :

    Trained on Juggernaut X with 347 photos of Elizabeth Olsen. Tested on Juggernaut X, Juggernaut v7, RealismEngine 2, RealVisXL3! Use with keyword : "elixolsen" . Use around strength 0.85-1.0. CFG 5.0-7.0. Clipskip 1. Can be used for example as follows:

    Positive : {Artstyle}, {Character and scene description}, elixolsen, <lora:eliolsen_juggerX_xl_8_standard_wocap_merger_lastmodel_120_04_06-elixolsen:0.95>

    Negative : ugly, deformed, airbrushed, photoshop, rendered, (multiple people), child

    SDXL v6.0 Juggernaut X :

    Trained for Juggernaut X with 320 photos of Elizabeth Olsen. Use with Juggernaut X, Juggernaut v7 or RealismEngine 2. Works best with Juggernaut X. Use with keyword : "elixolsen". Can be used for example as follows:

    Positive : {Artstyle}, {Character and scene description}, elixolsen, <lora:eliolsen_juggerX_v7_standard_wocap_merger_27_74_98_02_03_05-elixolsen:1>

    Negative : ugly, deformed, airbrushed, photoshop, rendered, (multiple people), child

    SDXL v5.0 160mb :

    Trained on 150 even more consistent (2015-2017) photos of Elizabeth Olsen with a smaller network dimension (32 instead of 64) to allow for smaller model size by half. Use with keyword : "elixolsen"!

    SDXL v4.0:

    Trained on 347 high quality photos of Elizabeth Olsen between 2015-2019 to ensure better facial consistency. Slight likeness improvement.

    SDXL v3.0:

    Lora trained on 199 images of Elizabeth Olsen and captioned by GPT-4 Vision. Lora strength should be between 0.8-1.2.

    SDXL v2.0:

    Lora retrained on 100 images of Elizabeth Olsen with SDXL 1.0 base and an improved Lora architecture to increase flexibility and likeness. The recommended strength on ComfyUi is 0.9-1.1.

    SDXL v1.0:

    Lora trained on 100 images of Elizabeth Olsen with SDXL 1.0 base. The recommended strength on ComfyUi is 0.9-1.1.

    Description

    TRAINED ON CIVITAI.

    All my images were tested directly in FLUX.1 [dev] (fp8) and should work on approx. 12 GB VRAM cards on FORGE (with fp8, clip_l and tf5_xxl as usual). Also works with NF4.

    FLUX v.1 (Olsen in 2012) :

    Trained on FLUX.1 [dev] with 70 photos of Elizabeth Olsen in 2012 with detailed GPT-4 captions. Tested on FLUX Dev (full) and FLUX fp8 ! Use around strength 0.8-1.0. Distilled CFG 3.5 and CFG 1.0 (without negative prompt). Clipskip 1. Can be used for example as follows:

    Positive : {Artstyle, Character and scene description in usual FLUX fashion}, <lora:Elizabeth_Olsen_2012_FLUX_epoch_46:1>

    FAQ

    Comments (13)

    MikeflowerAug 17, 2024· 1 reaction
    CivitAI

    😍 👍🏻

    steffangund
    Author
    Aug 17, 2024· 1 reaction

    Thanks!

    BillybobbroAug 18, 2024· 1 reaction
    CivitAI

    My Fav so far. Getting absolutely fantastic results from this.

    steffangund
    Author
    Aug 18, 2024

    Glad to hear!

    jeriffAug 23, 2024· 1 reaction
    CivitAI

    Could u pls share the lora training method?

    steffangund
    Author
    Aug 23, 2024· 1 reaction

    I just use the CIVITAI trainer. It costs approx 2000 Buzz per model. I dont change anything about the default settings other than the number of epochs so that I have a good 1000-2000 steps.

    @steffangund How many image do you use? And what image description process do you use?

    steffangund
    Author
    Sep 9, 2024

    @challasvarias01106 As written right below the images I used 70 images all taken in 2012 and used GPT-4 vision api to caption them with detail. Then I reaqd through some of them to make sure no glaring errors were made.

    challasvarias01106Sep 10, 2024

    @steffangund Thank you for the answer! What's is your recommended distribution between close up, upper body and full body photos if in your case you are using 70 images?
    I still don't get the correct proportions of the number of the type of images should I use in my dataset.

    steffangund
    Author
    Sep 10, 2024· 1 reaction

    @challasvarias01106 Depends on what you want. I always like to go something like 50/25/25 for closeup/mid shot/full body. If you want her lkeness to be perfect but with not perfect flexibility you can go something like 70/30 face closeup/mid shot. I have noticed that FLUX is significantly better at generalizing i.e. even if you use more face it will be able to generate good wide shots. SDXL is more picky.

    challasvarias01106Sep 10, 2024

    @steffangund Thank you for your time

    MinimumAsk4755962Aug 27, 2024
    CivitAI

    Still one of the best Flux Loras out there. Absolutly insane pictures with an 18mb LORA ♥️ Keep it up bro!

    PS: Would love to see your Meghan Markle LORA converted to Flux 👀

    Thank you 🙏🏼