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
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python emu_inference.py --instruct --ckpt-path $Instruct_CKPT_PATH
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## Citation
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If you find Emu useful for your your research and applications, please consider citing:
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python emu_inference.py --instruct --ckpt-path $Instruct_CKPT_PATH
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```
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## Acknowledgement
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We thank the great work from [LLaMA](https://github.com/facebookresearch/llama), [BLIP-2](https://github.com/salesforce/LAVIS), [Stable Diffusion](https://github.com/CompVis/stable-diffusion), and [FastChat](https://github.com/lm-sys/FastChat).
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## Citation
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If you find Emu useful for your your research and applications, please consider citing:
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