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
| BASE_DATA_DIR="path/to/basedata" | |
| BASE_CKPT_DIR="path/to/sd2_ckpt" | |
| export CUDA_VISIBLE_DEVICES=3 | |
| python train_s1.py --config config/train_s1.yaml \ | |
| --base_data_dir $BASE_DATA_DIR \ | |
| --base_ckpt_dir $BASE_CKPT_DIR \ | |
| --output_dir log/stage1_bs8 \ | |
| --no_wandb \ |