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
| # Last modified: 2025-01-14 | |
| # | |
| # Copyright 2025 Ziyang Song, USTC. All rights reserved. | |
| # | |
| # This file has been modified from the original version. | |
| # Original copyright (c) 2023 Bingxin Ke, ETH Zurich. All rights reserved. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| # -------------------------------------------------------------------------- | |
| # If you find this code useful, we kindly ask you to cite our paper in your work. | |
| # Please find bibtex at: https://github.com/indu1ge/DepthMaster#-citation | |
| # More information about the method can be found at https://indu1ge.github.io/DepthMaster_page | |
| # -------------------------------------------------------------------------- | |
| import os | |
| def is_on_slurm(): | |
| cluster_name = os.getenv("SLURM_CLUSTER_NAME") | |
| is_on_slurm = cluster_name is not None | |
| return is_on_slurm | |
| def get_local_scratch_dir(): | |
| local_scratch_dir = os.getenv("TMPDIR") | |
| return local_scratch_dir | |