Video-to-Video
Diffusers
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video-editing
streaming
quantization
int8
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Instructions to use kylinfires/Joy-face_change_optimized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kylinfires/Joy-face_change_optimized with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kylinfires/Joy-face_change_optimized", 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
File size: 120 Bytes
b9fc164 | 1 2 3 4 5 6 7 8 | import torch
PRECISION_TO_TYPE = {
"fp32": torch.float32,
"fp16": torch.float16,
"bf16": torch.bfloat16,
}
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