Instructions to use ModelsLab/blipdiffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ModelsLab/blipdiffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ModelsLab/blipdiffusion", 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:
- 385db010fc8173b62ad4e9a76124452e0756525247555cc6ca4e6209c3157e1a
- Size of remote file:
- 3.44 GB
- SHA256:
- c42d7cf4e4f028e3c955e13f4406231c946b602329de281b67c214f5efcb5137
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