Instructions to use WALIDALI/bekitoonly with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WALIDALI/bekitoonly with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("WALIDALI/bekitoonly", 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:
- 555bc95ec6c5bc1ef3596440acf6d0558326898b7e7dc0a5f15fcda99432893e
- Size of remote file:
- 246 MB
- SHA256:
- 272c6609469504b6607b8df206b3056395fe64d2edc5a2de57cc22548104aa0d
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