Instructions to use alppo/amuse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use alppo/amuse with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("alppo/amuse", 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
Download training_state.pt from alppo/amuse: direct link, hf CLI and curl.
- Browser
- Download file 944 MB
-
https://huggingface.co/alppo/amuse/resolve/main/training_state.pt
- Command line
-
hf download hf://alppo/amuse/training_state.pt
-
curl -L -o training_state.pt https://huggingface.co/alppo/amuse/resolve/main/training_state.pt
944 MB
- Xet hash:
- eb21ed378ffadcb54570d3d5527863e3c68419dfad1672f3c6eacf4c3c57ce08
- Size of remote file:
- 944 MB
- SHA256:
- 7e4ebf42c79280e23f0287284188250f748dd9b9b17084c1fb28a2c463e9adc7
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