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:
- f5dc12ad880b4f4e41b5a0d79fa1a77ae6e6fa4fc8b6a63880a07aad1bb427fe
- Size of remote file:
- 3.81 GB
- SHA256:
- 9307cd7aff6c6a22945c19723e0426f5631ebb31406d7d7021a2aa7127cc69fe
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