Instructions to use timduck8/CA002v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use timduck8/CA002v2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("timduck8/CA002v2") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 25913df2ea86da1c0f7f86d0ee2caef5c298c8fc886372ccc6c8f47a0ae2f8c0
- Size of remote file:
- 228 MB
- SHA256:
- d9322aad79e347f6b31a09501df0807e0dbcfd6365c1edfe2fc2201280ad117e
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