Instructions to use ayushtues/blipdiffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ayushtues/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("ayushtues/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
Commit History
Update README.md d1b2c34
Update README.md 4b272e9
Update README.md d91b6ac
Create README.md 6ee0429
Upload model_index.json b744de5
Upload model_index.json 1baed62
Upload 2 files 42d3b0a
Upload config.json 6cc6f03
Upload model_index.json 8d0dcc8
Upload model_index.json ad84916
Add canny controlnet 7a044df
Update 2a8458a
Add initial components 19f7956
Ayush Mangal commited on