Instructions to use m-a-p/MIO-7B-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use m-a-p/MIO-7B-Base with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("m-a-p/MIO-7B-Base", 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:
- 1dee7727a54e786ddef919a17e7739c75d9998af377017f7694cede6d3d31773
- Size of remote file:
- 1.25 GB
- SHA256:
- af1df349296ce2b779c49f21c540f28a75e35a6049c0e8e87ec6703023ebebf0
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