Text-to-Image
Diffusers
Safetensors
English
StableDiffusionPipeline
Anime
Animation
Style
stable-diffusion
stable-diffusion-diffusers
Instructions to use Yntec/Based64 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/Based64 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Yntec/Based64", 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:
- 00bea0706c7096a21b5e94f558f19adbd6a5854cefecef855e34a602228e547e
- Size of remote file:
- 2.13 GB
- SHA256:
- d1ae300a300d4fe1ad9a684de5218f999364c257c67e7961202435c970f5caaf
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