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:
- 17b2caf4d1e602a3a5ef63bb297241d7e71314e37b6a95130a7905ade961c9fd
- Size of remote file:
- 9.72 GB
- SHA256:
- 013278668a6c876e12d17513b2c905ec58ba65eb1f2b4791282f9919fb645d24
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