import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Wan-AI/Wan2.2-I2V-A14B", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("profpeng/blinkfrontdoggy")
prompt = "The video begins with a close-up of a woman. The video then jumpcuts to the same woman now having sex with a man in doggystyle position in the the same location. She is positioned standing, while the man stands behind her, The man is muscular his hands are wrapped around the womans's stomach holding her upright while embracing her from behind, he holds her close as he thrusts into her. As the scene progresses, she moves rhythmically with him. she is fully nude. the man aggressively rams his hips into her."
image = pipe(prompt).images[0]frontaldoggy
- Prompt
- The video begins with a close-up of a woman. The video then jumpcuts to the same woman now having sex with a man in doggystyle position in the the same location. She is positioned standing, while the man stands behind her, The man is muscular his hands are wrapped around the womans's stomach holding her upright while embracing her from behind, he holds her close as he thrusts into her. As the scene progresses, she moves rhythmically with him. she is fully nude. the man aggressively rams his hips into her.
Trigger words
You should use doggystyle position to trigger the image generation.
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Wan-AI/Wan2.2-I2V-A14B