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:
- 2df25542a22d8b97bc8bacecba2c6466eb7b4acf4050b463e90adfb003dadb46
- Size of remote file:
- 9.5 GB
- SHA256:
- 33521ab5872daaa38ac4cd9437f9d859bc0d84c02a250b2d9bd0e218cbb78c7d
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