Instructions to use MirageML/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MirageML/test with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MirageML/test", 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 MirageML/test: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/MirageML/test/resolve/refs%2Fpr%2F2/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://MirageML/test@refs/pr/2/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/MirageML/test/resolve/refs%2Fpr%2F2/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- 2963b018f6d79ce5f2939da555eefb64a30494df4b340d5359219c19e20547f1
- Size of remote file:
- 3.44 GB
- SHA256:
- 25476d104b2f0b31c8b9ae7846834518657b53e523df22a659add4b5e5f93bcb
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