Instructions to use Zlikwid/zlikwid with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Zlikwid/zlikwid 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/zlikwid", 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
- Draw Things
- DiffusionBee
- Xet hash:
- 971d3050089990fba3c59f3a898065259870abe658b92dee86c5bc5b5df87ea8
- Size of remote file:
- 492 MB
- SHA256:
- ef24639c5bab833ac5ab76198415cd930832ef0e283a69d57e28504394f55f00
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