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:
- 9819f55aa2654c961c3e030dc55ae286d9c498ab40a313de54427fe45e7c41fa
- Size of remote file:
- 5 GB
- SHA256:
- 74fe06f8ac5baf1fe8c39a2dbce5f340f63a7ef6aec544b4b62e29a233a30946
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