Instructions to use orrzohar/BLIP3o-4B-Diffusion-Decoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use orrzohar/BLIP3o-4B-Diffusion-Decoder with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("orrzohar/BLIP3o-4B-Diffusion-Decoder", 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:
- 3e21f7e7bd2c306e53d15173acec153d10d54d23ce5df61d3e1c0d56a72e8525
- Size of remote file:
- 167 MB
- SHA256:
- 2741af7e84fe3b0a7aee02f89fa34c0858ed55f5782aab5931b94938983652da
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