Instructions to use flax/redshift-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use flax/redshift-diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("flax/redshift-diffusion", 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
Commit History
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Fix deprecation warning by changing `CLIPFeatureExtractor` to `CLIPImageProcessor`. (#3)
- Fix deprecation warning by changing `CLIPFeatureExtractor` to `CLIPImageProcessor`. (1905ce32e1c081f4712503239150b70d63583144)660d645
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Add `scale_factor` to vae config. (#2)
- Add `scale_factor` to vae config. (f08b421051cf62912ae16e93c3fd1bfbea7129de) Co-authored-by: Suraj Patil <valhalla@users.noreply.huggingface.co>f70e9d2
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Add `clip_sample=False` to scheduler to make model compatible with DDIM. (#1)
- Add `clip_sample=False` to scheduler to make model compatible with DDIM. (eba54b51c7698a202892f11d7df6b3d7c0a700b0) Co-authored-by: Patrick von Platen <patrickvonplaten@users.noreply.huggingface.co>b232a83
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Update unet/config.json
a7da764
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Create README.md
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flax
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initial commit
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