Instructions to use WT-MM/Mei with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WT-MM/Mei with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("WT-MM/Mei", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
Download unet/diffusion_pytorch_model.bin from WT-MM/Mei: direct link, hf CLI and curl.
- Browser
- Download file 3.46 GB
-
https://huggingface.co/WT-MM/Mei/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://WT-MM/Mei/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/WT-MM/Mei/resolve/main/unet/diffusion_pytorch_model.bin
3.46 GB
- Xet hash:
- 59257918a2657ff91d6b2961f513da19c0cd31be27858bf133505cba53ab2244
- Size of remote file:
- 3.46 GB
- SHA256:
- df1ee70456a89b328bcd62d6a21076ea9172a945a93a86567f149860771d0c63
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