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:
- 0ea9bef789b0dce896be87dfb0c458e7cb8b2e1b91542ecc97bde420e83cc55c
- Size of remote file:
- 351 MB
- SHA256:
- 9c14c7620d6f60372168b469b8dc9a0da10b30ba308b3499e687315a9cf0aa84
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