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
File size: 354 Bytes
4b7b610 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | # 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]
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