Instructions to use harmonai/maestro-150k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use harmonai/maestro-150k with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("harmonai/maestro-150k", 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
- Xet hash:
- 08b0b7b2dc2321e00e134edaffcf78b42f941ec6db89887db27dd15a3ca23b32
- Size of remote file:
- 886 MB
- SHA256:
- 5d1a00adfc0452da32fb8fd381322a158e87a2c3afe248b4dd3f15f509690894
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