Instructions to use tiny-random/minimax-h3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tiny-random/minimax-h3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("tiny-random/minimax-h3", 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:
- 88dd1898e37696f2ecc62ee0e6719937f9403ebfa52ad525afb0b0f821c4e824
- Size of remote file:
- 11.4 MB
- SHA256:
- 170c542379436ef9d4574ad325af3bf4c8c3ef295951fdc060a319a905bb7ff2
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