Diffusers
Safetensors
PyTorch
AudioDiffusionPipeline
unconditional-audio-generation
diffusion-models-class
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]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()))
- Downloads last month
- 3
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support