Instructions to use BAAI/Emu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BAAI/Emu with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BAAI/Emu", 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
First model version
Browse files- Emu-instruct.pt +3 -0
- Emu-pretrain.pt +3 -0
Emu-instruct.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:43727b37d6d2d64d8a323ac3fc4c180e12ff385fa846fbfd81a31671b70a5794
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size 28469727530
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Emu-pretrain.pt
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oid sha256:1c0ccac775918d5cb2412de2b20d28b983f6b64b96d8a350416001eb817f1cb5
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size 28416988239
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