Text-to-Image
Diffusers
UniDiffuserPipeline
image-to-text
image-captioning
image-variation
text-variation
multi-modality
generative model
Instructions to use thu-ml/unidiffuser-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use thu-ml/unidiffuser-v0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("thu-ml/unidiffuser-v0", 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 Settings
- Draw Things
- DiffusionBee
Download autoencoder_kl.pth from thu-ml/unidiffuser-v0: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/thu-ml/unidiffuser-v0/resolve/main/autoencoder_kl.pth
- Command line
-
hf download hf://thu-ml/unidiffuser-v0/autoencoder_kl.pth
-
curl -L -o autoencoder_kl.pth https://huggingface.co/thu-ml/unidiffuser-v0/resolve/main/autoencoder_kl.pth
335 MB
- Xet hash:
- 9e7c62686a00a2152e50bb95c463f8cf4f06139d48b33695d66f9e2eb11850db
- Size of remote file:
- 335 MB
- SHA256:
- d9b1dd54896562748f6b048b88e91ffb6bb02be711f90711ce62ca1629218be2
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