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:
- 37e5393769a8815f61bd755028868448c8ce997194f4aaa1123817fc48a637cd
- Size of remote file:
- 66.7 MB
- SHA256:
- 5a9928676863a1a8c2a9ec549e5cc85f7ad986587c5ec1b7597aaa5db2c59a3c
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