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:
- d10ac20a424cbfe3f4d5e631aa08b39aa48335c37bee9dac4c9dee1fde3ba5a6
- Size of remote file:
- 4.84 GB
- SHA256:
- 0186175da67d2d46a7cdffd5f5e6fb083b758523fd91d433b0d8c17ed13eca10
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