Instructions to use KawaiiApp/anythinv3-vae-handler with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use KawaiiApp/anythinv3-vae-handler with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("KawaiiApp/anythinv3-vae-handler", 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
hmm
Browse files- handler.py +0 -2
handler.py
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@@ -38,8 +38,6 @@ class EndpointHandler():
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height = data.pop("height", 512)
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width = data.pop("width", 512)
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inference_steps = data.pop("inference_steps", 25)
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guidance_scale = data.pop("guidance_scale", 7.5)
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# Run inference pipeline
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height = data.pop("height", 512)
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width = data.pop("width", 512)
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inference_steps = data.pop("inference_steps", 25)
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guidance_scale = data.pop("guidance_scale", 7.5)
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# Run inference pipeline
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