CivArchive

    This Lora is made to enhance the ability / quality to create anthro and furry

    but it works also for all kind of other fantasy creatures and animals too

    the range that it can handle for example the Wan 2.2 V2 Lora is from comic and drawing towards real photos .

    i made the lora for Hunyuan Video , WAN 2.1 and 2.2 (SFW and NSFW)

    Furry Enhancer Hunyuan V1

    The Hunyuan Video version is trained for Text to Video (T2V) but i also tested it on Image to Video its also working with it very good but not made for that.

    All example images for the Hunyuan Video are made T2V

    Its also compatible with Ratatoskr Hunyuan

    Wan 2.1 I2v and T2V V1

    The Wan 2.1 has 2 different models

    I2V and T2V

    the image to video is in most cases the model of choice for Wan

    for the Text to Video Variant please read the description.

    Its also compatible Ratatoskr WAN 2.1 (ITV) and will for sure increase the quality especially in the NSFW Area.

    I also tested the I2V Lora with Wan 2.2 it seems to enhance the result too but very experimental

    Wan 2.2 I2V and T2V V1

    This enhancer version is for Wan 2.2 its splitted in basically 2 Loras: low and high noise

    both loras for I2V are trained on the same dataset. I its my own dataset before i trained with the wan 2.1 Lora but add more pictures and videos

    it's completely synthetic so no real persons or art is used for the dataset.

    whats the pros of this lora compared to the wan 2.1?

    • more consistent

    • more specimen

    better in sfw and nsfw

    i recommend using both loras and use the workflow in the training folder Note: your resolution needed to set between 0.4 (480P) and 0.92 (720p) overwise the lora generate backscreens or other failures.

    for strength i prefer the full 1.0 strength its tested

    its tested with the original wan 2.2 model

    also in a short test with my Ratatoskr WAN 2.2 Hybrid v1.0 WIP model (use only the high noise version with that model)

    for technical data about Wan 2.2 visit there official site here:

    V2 Furry Enhancer High Noise

    Changes compared to V1

    • more consistent

    • more specimen

    • better overall movements

    • more stable overall

    • way better with comic and anime than V1

    better in sfw and nsfw

    i recommend using the V1 Version of the WAN 2.2 I2V V1.0Low Noise

    Note: I used for example the old workflow for this model to compare V1 with V1 if you like the newest workflow download the training folder.

    Important for this workflow is to keep the resolution between 0.4 and 0.92 (480p - 720p)

    V3 High Noise and Low Noise

    This enhancer version is for Wan 2.2

    its trained my own dataset

    it's completely synthetic so no real persons or art is used for the dataset.

    the biggest change in this dataset is its now completely trained on videos

    Changes compared to V2

    • trained now on over 650 Videos

    • better overall movements

    • more emotions

    • way better with comic and anime than V1 and V2

    better in sfw and nsfw

    for this Version there is also an newtrained Low Noise Model

    LTX2.3 Version (WIP Preview V0.1)

    this is an preview version of the first attempt to train the ltx 2.3 model with a very limited dataset

    so it's more like an technical demonstration / trial than a fully trained lora.

    So don't expect best results yet it's highly experimental.

    for workflow i have also added an experimental workflow.

    LTX2.3 Version V1 Lora Pack

    This is the First full Release Version of the LTX Version of Furry Enhancer Video.

    Better to say it's an model pack because

    V1.1 is made based on ltx 2.0 training setup so best for the LTX 2.0 model

    V1.215 its the main model trained specifically for the ltx 2.3 Version so start usually with that lora

    V1.22 More advanced in training but has sound issues.

    V1.3 experimental (wip) model trained in different training modes (heavy sound issues)

    you find the used workflows and the different model versions in the "training folder"

    the loras are tested on the dev version and the distilled variant.

    what has changed to preview?

    • Trained on the full video database (V1.2 and up) at around 700 videos instead of only 40 videos

    • Also trained on my photo database of ratatoskr overall over 10k pictures

    • Trained for i2v and t2v

    • better overall knowledge and movement .

    Note: this is still in development because most of the trained videos are based on my wan2.2 database so its planned to train an v2 this year with video output of that model.

    also i don't have my own workflow done yet so it depends on other workflow don by afroman4peace and akinson

    LTX2.3 Version V2.4

    I have decided to retrain the dataset on a far advanced system now its trained on a server with an rtx6000 pro blackwell for more than a week 24/7 (and yes this was expensive)

    so what has changed from V1 to V2.4?

    • the trained video resolution is now at 720P constant

    • image training did improved from 1024p to 1536p

    • added 120 new sound videos for training especially for speech and jaw movements.

    • seperated videos with sound and not sound and trained in different databases

    • trained for T2V and I2V in stages so its nearly equally trained for both now

    • added new pictures to database too but more important overworked the captions fitting better for video training

    For settings and workflow i have added my example videos in the training folder the images and some videos has the metadata just put them into comfy

    on my workflows was the loral at best between 0.8 and 1.0

    the lora is trained on the dev model but also tested for the distilled version

    for now still don't have my own workflow done yet so it depends on other workflow don by afroman4peace and akinson

    please support my work with an like and look on my other loras and models too

    the newest workflow download the training folder.

    in all videos the metadata is also included just download the video and put it into Comfy

    Important for this workflow is to keep the resolution between 0.4 and 0.92 (480p - 720p)

    if you like to support me please give a like and Check out my other models.

    Making such loras take a huge amount of cost and time please support my work with a like.

    and please check out my other models and loras too ;-)

    made by freek22

    Description

    I have decided to retrain the dataset on a far advanced system now its trained on a server with an rtx6000 pro blackwell for more than a week 24/7 (and yes this was expensive)

    so what has changed from V1 to V2.4?

    • the trained video resolution is now at 720P constant

    • image training did improved from 1024p to 1536p

    • added 120 new sound videos for training especially for speech and jaw movements.

    • seperated videos with sound and not sound and trained in different databases

    • trained for T2V and I2V in stages so its nearly equally trained for both now

    • added new pictures to database too but more important overworked the captions fitting better for video training

    • stable video output up to 25 seconds for i2v and t2v

    For settings and workflow i have added my example videos in the training folder the images and some videos has the metadata just put them into comfy

    on my workflows was the loral at best between 0.8 and 1.0

    the lora is trained on the dev model but also tested for the distilled version

    for now still don't have my own workflow done yet so it depends on other workflow don by afroman4peace and akinson

    please support my work with an like and look on my other loras and models too

    FAQ

    Comments (13)

    N0n4m3Apr 18, 2026
    CivitAI

    @freek22 Do You have numbers for 5090 vs RTX6000 Pro Blackwell training speed?

    Please do correct me if I'm wrong but I do assume that these are essentially same chips just different VRAM config... and quadrupled price for RTX6000.

    freek22
    Author
    Apr 18, 2026· 1 reaction

    i don't have sadly but with the chosen training settings i was always above 84gb vram and sometimes at 94gb

    freek22
    Author
    Apr 18, 2026· 1 reaction

    but i bet you are correct about it

    brand175Apr 18, 2026· 2 reactions

    I have a 5090 and I have seen someone online use a rtx6000, it runs basically the same speed from ltx training. The only difference is the VRAM size and you can push the settings further because of it. Other than that, it runs the same in training unless you count the extra VRAM acting as a buffer. In terms of 2x 5090's and 1 rtx6000. I have no idea. Being VRAM maxed is what kills the gen time on the 5090, faster RAM will help a ton on longer training.

    N0n4m3Apr 18, 2026

    Ok, than waiting for Q.ANT photonic GPUs.

    Good that, after purchasing 5090, I still have some spare organs...

    brand175Apr 18, 2026· 1 reaction

    @N0n4m3 from my experience, going to a rtx2080 to a rtx5090. Having more RAM to make up for the VRAM is more than justified. I was able to run Flux dev full model on a 8GB card when the minimum is 24GB to run it. When I compared the results to the 2080, it was only 4x slower than the 5090 even when the VRAM was full. The rtx5090 was already 3 to 4 times faster anyways than the rtx2080. The thing is that their is a setting in AIToolkit which allows you to use RAM to make up for the VRAM, and I don't know the limit as I don't have enough RAM to find out.

    freek22
    Author
    Apr 19, 2026· 1 reaction

    @brand175 right it helps especially to train huge datasets fast this is why I choose that way than using my own system again for training that has an 5070ti and 2xA4500 GPUs it saved literally weeks of time

    N0n4m3Apr 19, 2026

    @brand175 @freek22 Using it I was able to train dataset with 50+ vis of up to 10-15sec @ 24fps, But this doesn't solve really a problem because:

    1. RAM is as much expensive nowadays as GPUs

    2. with direct storage and synthetic data used for training nowadays SSD skyrocket also...

    But it is still slow, going between RAM<->VRAM.

    Anyway like I said earlier good that I have some spare organs because purchasing 128GB RAM is almost as expensive as purchasing RTX5080... crazy world we are living now.

    EDIT: correction it is as expensive as RTX 5090 ... what is happening here ???

    FoxdudeApr 19, 2026
    CivitAI

    Can't download the model; "Error getting file" :(
    My first comment about this also disappeared.
    I guess CivitAI has issues.

    freek22
    Author
    Apr 19, 2026· 1 reaction

    yes its civit but i guess it will working soon again

    celticwolf72Apr 26, 2026
    CivitAI

    Using the built-in workflow for WAN 2.2 I2V, with the high and low noise put in the diffusion models, I got the following error:

    RuntimeError: ERROR: Could not detect model type of:

    Any ideas?

    freek22
    Author
    Apr 26, 2026

    the problem here is over the time comfy has changed a lot of things so its hard to say what the reason is btw i also recommend using in most cases to switch to the ltx variant of the lora

    celticwolf72Apr 26, 2026

    I'm still puzzling out how to use the ltx version. Every time I add it to the workflow, the image fuzzes out.