Instructions to use alaub/10Eros-Max-fl2va-diffusers-transformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use alaub/10Eros-Max-fl2va-diffusers-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("alaub/10Eros-Max-fl2va-diffusers-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:
- 11293558eeb0448a22d4b6549131130f74d98d208db6edb599600b06c7347754
- Size of remote file:
- 5.72 GB
- SHA256:
- d072b4cda3ae2975db52ca445fb3e560336992addc1421fdfb8c007cd164c22d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.