Wan 2.2 Spoon LoRA by MQ Lab
This LoRA from MQ Lab was generated by selecting an appropriate training method, curating many datasets to avoid bias, and manually writing captions.
MQ Lab's LoRA will continue to evolve. I will continue to add more datasets, improve quality, and provide new versions.
Prompt ex
mqlspn_a. A young woman and a man sex scene. The two of them are lying sideways on a bed. The man is positioned behind the woman, thrusting his penis back and forth in her vagina. The woman and the man are nude.
Tips
When using with Character LoRA, it's a good idea to write a prompt about the character's appearance.
The output video is blurry because there aren't enough low-noise processing steps. Please increase the number of steps.
If the movement is too fast, set the FPS to 16.
MQ Lab has recently launched a paid membership service, which allows users to download LoRA, which is not available on Civitai.
You can follow the latest developments on Discord.
Description
FAQ
Comments (15)
I2v please
most t2v loras like this work just fine in i2v workflows
I think you've put the details from your other recent "spooning" lora on this page. If you get a chance could you give the trigger word etc. for this one?
In case you haven't found it already, from the clip description...
mqldgy_a. A woman and a man sex scene. The woman is on all fours on a sofa. The man is kneeling behind the woman, thrusting his penis back and forth in her vagina.
Ah - didn't think to check the details of the example vid. Yeah. Thanks for this!
Hi, why does the description say spoon lora?
Great! Finally some results. Working fine.
need i2v
Agreed
Agreed
"mqldgy_a. A woman and a man sex scene. The woman is on all fours on a sofa. The man is kneeling behind the woman, thrusting his penis back and forth in her vagina."
I've tried all the doggy style loras, this one is the best.
Thank you for making it :)
where is all casting models.?
wonder if now that civitai.red is separated out, if casting models can return?
Details
Files
mql_doggy_a_wan22_t2v_v1_high_noise .safetensors
Mirrors
mql_doggy_a_wan22_t2v_v1_high_noise (1).safetensors
mql_doggy_a_wan22_t2v_v1_high_noise .safetensors
mql_doggy_a_wan22_t2v_v1_high_noise .safetensors
Wan-2.2-mql_doggy_a_wan22_t2v_v1_high_noise .safetensors
mql_doggy_a_wan22_t2v_v1_high_noise .safetensors
mql_doggy_a_wan22_t2v_v1_high_noise .safetensors
mql_doggy_a_wan22_t2v_v1_high_noise .safetensors
mql_doggy_a_wan22_t2v_v1_high_noise.safetensors
mql_doggy_a_wan22_t2v_v1_high_noise .safetensors
mql_doggy_a_wan22_t2v_v1_high_noise .safetensors
mql_doggy_a_wan22_t2v_v1_high_noise .safetensors
mql_doggy_a_wan22_t2v_v1_high_noise .safetensors