Instructions to use dekes1/cindycfr13 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dekes1/cindycfr13 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("krea/Krea-2-Raw", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("dekes1/cindycfr13") prompt = "A golden labrador running across a sunny farm, a pickup truck on a dusty road far behind, cindycfr11" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 1de3d7c43b1bc388b5af73382d5b6a63819bce9eef1f016b043f662caedebaf7
- Size of remote file:
- 195 MB
- SHA256:
- c49ee86223067c9e3cab95563dc0accef7457dbd8ca23f533000929b7353d70c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.