Instructions to use timduck8/Slammin_Assertive_Cowgirl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use timduck8/Slammin_Assertive_Cowgirl 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/Wan2.1-I2V-14B-480P", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("timduck8/Slammin_Assertive_Cowgirl") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 69554e7ad828df19603107f0401ef7a1b5a7d07e1ed9ee3474b2a85c7df1f6e3
- Size of remote file:
- 307 MB
- SHA256:
- e183d0756075cb350fa5874690f6bbea160abf632f4f93d290c4ee1cf74d5c91
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