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
| set -e | |
| set -x | |
| export CUDA_VISIBLE_DEVICES=5 | |
| python evaluate.py \ | |
| --base_data_dir path/to/basedata \ | |
| --dataset_config config/dataset/data_hypersim_test.yaml \ | |
| --alignment least_square_sqrt_disp \ | |
| --output_dir output/hypersim/final \ | |
| --checkpoint ckpt/eval \ | |
| --processing_res 0 \ | |
| --seed 1234 \ | |