Instructions to use inclusionAI/Ming-flash-omni-2.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use inclusionAI/Ming-flash-omni-2.0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("inclusionAI/Ming-flash-omni-2.0", 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
Download model-00039-of-00042.safetensors from inclusionAI/Ming-flash-omni-2.0: direct link, hf CLI and curl.
- Browser
- Download file 5 GB
-
https://huggingface.co/inclusionAI/Ming-flash-omni-2.0/resolve/refs%2Fpr%2F1/model-00039-of-00042.safetensors
- Command line
-
hf download hf://inclusionAI/Ming-flash-omni-2.0@refs/pr/1/model-00039-of-00042.safetensors
-
curl -L -o model-00039-of-00042.safetensors https://huggingface.co/inclusionAI/Ming-flash-omni-2.0/resolve/refs%2Fpr%2F1/model-00039-of-00042.safetensors
5 GB
- Xet hash:
- ee7b090b5aa76618bb639ef99cb6bd8d92bc1692e2a61aada79f9a7b40335734
- Size of remote file:
- 5 GB
- SHA256:
- b746d362a232d9d9af4a0c366ce8337828ebc82039b8833ad81a6bc738f25ee9
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