Instructions to use ibyteohdear/10Eros-Max-Transformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ibyteohdear/10Eros-Max-Transformer with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ibyteohdear/10Eros-Max-Transformer", 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
- Xet hash:
- 1f76ac965dc9b1f1b159fefc176d22e636f88b8300d9340f269ff25df6a99a9b
- Size of remote file:
- 8.33 GB
- SHA256:
- 9db3c9bd5e345266177a233c2a11f1dd7bb9c7e60e340f66afcdf0c571f0dd01
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