Wan POV Doggy Style (i2v)
POVdog.safetensors LORA / Wan Video
- Model Name
- Wan POV Doggy Style (i2v)
- Version
- v1.0
- Creator
- lazerblazer
- Size
- 513.87 MB
- Downloads
- 2,207
- Trigger
- POVdogA POV video showing man having sex doggy style sex with a woman.
- BTIH
- 0DDD19AF10F64AAA740EAA9DDC884641DE3594D3
- BTMH
- 019917423E2C7B3848027F1F166B17E50140FE1A1EBADF530B3683AE87CFEB4F
- SHA256
- 6B51BBA3B7F80233407A318257A16DAF5D4CBD2A5F2CF18E148D8B0E5858F722
- Upload Date
- about a year ago
- Uploader
- CivitasBay.org
- Status
- 5 Seeders0 Peers
Trained for image2video generation, not tested on text2vid
v1.1 UPDATE
Version 1.1 is a significant improvement of v1.0. It produces the doggy style motion consistently. The LoRA was trained on vertical videos - it has been reported that wide aspect videos may have some issues. Please leave some feedback if you have issues with it.
Note: I noticed there can be some image artifacts that appear, usually on the ass. I think this is due to low resolution videos in my data set. I looked into improving the quality with AI upscaling, but ran into a lot off issues that ended up making the videos worse, so this will do for now.
Trigger word is POVdog. "A POV video showing a man having sex doggy style sex with a woman." and "Ass movement and bounce is emphasized" can help too.
I used aipinups69's https://civarchive.com/models/1358184/wan-21-penis-cock-dick-lora-t2v-i2v?modelVersionId=1534254 at strength 0.5 in my testing again and it worked great.
v1 -
This is my first attempt at training anything and is still a work in progress. It seems to work okay - some feedback on how to improve is always appreciated. I trained on 480p 14B, I am not sure if it works for the 720p version or not.
Trigger word is: POVdog. The phrase "A POV video showing man having sex doggy style sex with a woman." Was included in most of the training data as well.
In my testing I found this works better with aipinups69's https://civarchive.com/models/1358184/wan-21-penis-cock-dick-lora-t2v-i2v?modelVersionId=1534254 at low strength (0.4 - 0.5) to keep the man bits not looking too deformed.
I need to take a closer look to my training process and data set and will hopefully improve this in the week. Training took about 10 hours on two 4090s which seems a lot longer than other people have trained their models, so I definitely have some inefficiencies.
Let me know what y'all think!
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