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:
- 7847f7b5072a7b8bfb42d6f730e7a6ac5623a706e21dc1f6f0c7bba2f82ea7df
- Size of remote file:
- 9.5 GB
- SHA256:
- d6e8fd30d2103b1c41248431a612df73ccf28eb3550c821db7025b362521b2ee
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