Instructions to use andrewheins55/Ming-flash-omni-2.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use andrewheins55/Ming-flash-omni-2.1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("andrewheins55/Ming-flash-omni-2.1", 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:
- 06d36bc5398de95e1a17ff62b0b7ba20dd020995339a2c0ef5e4a91ec7e65b78
- Size of remote file:
- 5 GB
- SHA256:
- af19341964d43fc3da0f46d704f735251c20232b4a959f9979217d44ff95de29
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