Instructions to use Ching2602/blinktitjob with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Ching2602/blinktitjob with Diffusers:
pip install -U diffusers transformers accelerate
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("Ching2602/blinktitjob") prompt = "The video begins with a close up of a woman. The video then jumpcuts to the same woman kneeling in the same location with her breasts positioned around the man's erect penis as she moves them up and down in a sliding motion. she makes various facial expressions she looks like she is talking and has her eyes wide open with a crazy expression." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
blinktitjob
- Prompt
- The video begins with a close up of a woman. The video then jumpcuts to the same woman kneeling in the same location with her breasts positioned around the man's erect penis as she moves them up and down in a sliding motion. she makes various facial expressions she looks like she is talking and has her eyes wide open with a crazy expression.
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Wan-AI/Wan2.2-I2V-A14B