Diffusers
Safetensors
PyTorch
AudioDiffusionPipeline
unconditional-audio-generation
diffusion-models-class
Instructions to use Kevin3111/Electronic_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Kevin3111/Electronic_test with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Kevin3111/Electronic_test", 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
Model Card for Diffusion Models Class 🧨
这个模型是一个旨在生成 electronic 风格音乐的非条件性扩散模型
Usage
import torch
from diffusers import DiffusionPipeline
from IPython.display import Audio
device = "cuda" if torch.cuda.is_available() else "cpu"
print(f"device: {device}")
pipe = DiffusionPipeline.from_pretrained(
'Kevin3111/Electronic_test'
).to(device)
output = pipe(steps=50)
display(output.images[0])
display(Audio(output.audios[0], rate=pipe.mel.get_sample_rate()))
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