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:
- 53554b4f1a7e98e2019b2677553f0b7fd1c0b1d4e1bcf170de78631cb7c69031
- Size of remote file:
- 5 GB
- SHA256:
- 4499f51c9289f68c9e758b10ed4c68e9227d14272d702246f9524053540cd0b9
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