Instructions to use brianwithapp/cffcp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use brianwithapp/cffcp with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("brianwithapp/cffcp", dtype=torch.bfloat16, device_map="cuda") prompt = "cffcp" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- f8882ad2fb5561849f1a319a62adaf3120edc4fffa4df406df8b32ce1537fc50
- Size of remote file:
- 3.46 GB
- SHA256:
- fc9bac8ee8c7807014a4843b460a3f9eb54cc73835693d78ba098b7e435d7d97
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.