Instructions to use kmpartner/bkcncl-ft-test2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kmpartner/bkcncl-ft-test2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kmpartner/bkcncl-ft-test2", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d8456aae89e0d85fefa516dbac8db057f8aa17a95e441b873a605e018c8eb321
- Size of remote file:
- 378 MB
- SHA256:
- 0e744dbd9920f5ec8fd7aeca5237bd64327021ba073930135bf7b7a3c2d6ef8e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.