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:
- f248dd666e5dc93a366cb557928a9a04e1aeb5121815b8bae1c5eab9656fe667
- Size of remote file:
- 9.87 GB
- SHA256:
- cd18946322692ea742654eb9a5a84377059870882db495f722dce158c8c28f10
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