Instructions to use Hugol33/epi5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Hugol33/epi5 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Hugol33/epi5", 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:
- eea1d0fb0f6eceba7131dd8c7a5b9c36f4337e82ddeb7ec28820112109c3f2cd
- Size of remote file:
- 167 MB
- SHA256:
- 026863fa7189ee44d5e736ecb757fba58d846d9a0c479d00e0acbeaceb813bb0
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