Instructions to use zeyuren2002/EvalMDE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use zeyuren2002/EvalMDE with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("zeyuren2002/EvalMDE", 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
| # Author: Bingxin Ke | |
| # Last modified: 2024-05-17 | |
| from .trainer_s1 import DepthMasterTrainerS1 | |
| from .trainer_s2 import DepthMasterTrainerS2 | |
| trainer_cls_name_dict = { | |
| "DepthMasterTrainerS1": DepthMasterTrainerS1, | |
| "DepthMasterTrainerS2": DepthMasterTrainerS2, | |
| } | |
| def get_trainer_cls(trainer_name): | |
| return trainer_cls_name_dict[trainer_name] | |