Instructions to use Zlikwid/zlikwidcomplete2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Zlikwid/zlikwidcomplete2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Zlikwid/zlikwidcomplete2", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- bec1511991498a31735ca534f80e0db6fcb111126319f80ee9ad888b04974380
- Size of remote file:
- 3.44 GB
- SHA256:
- ef80058c2622fafcb2f8c52d1f5846d55966bead0d802f1873b034f454aec7ce
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.