Text-to-Image
Diffusers
UniDiffuserPipeline
image-to-text
image-captioning
image-variation
text-variation
multi-modality
generative model
Instructions to use dg845/unidiffuser-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dg845/unidiffuser-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dg845/unidiffuser-diffusers", 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
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 8a4e8b43dd1c9e78d395088cf8a5671f45d1df039c1bec08a80eb6d30d988e93
- Size of remote file:
- 511 MB
- SHA256:
- c8d2be17e1a581a8b04c298b76477673a42df5647bb9f4e685947cbab68f1c2f
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