Instructions to use haor/Evt_V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use haor/Evt_V2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("haor/Evt_V2", 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`. (#4)
- Fix deprecation warning by changing `CLIPFeatureExtractor` to `CLIPImageProcessor`. (f3f3b71bdf9a98892c33eca731423358c8be4db2) Co-authored-by: Patrick von Platen <patrickvonplaten@users.noreply.huggingface.co>bdfa477
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Add `scale_factor` to vae config. (#3)
- Add `scale_factor` to vae config. (80fa7ef121cfccd3c44574450fb8afb90568cd56) Co-authored-by: Suraj Patil <valhalla@users.noreply.huggingface.co>95eded3
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Correct `sample_size` of Stable Diffusion 1's unet to have correct width and height default (#1)
- Correct `sample_size` of Stable Diffusion 1's unet to have correct width and height default (3ed355b673f8ffdfa7a788452d2d60be5c7b861d) Co-authored-by: Patrick von Platen <patrickvonplaten@users.noreply.huggingface.co>02fef7f
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initial commit
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