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Running
on
Zero
import torch | |
import torchaudio | |
import spaces | |
from einops import rearrange | |
from stable_audio_tools import get_pretrained_model | |
from stable_audio_tools.inference.generation import generate_diffusion_cond | |
import gradio as gr | |
import os | |
from huggingface_hub import login | |
hf_token = os.getenv('HF_TOKEN') | |
login(token=hf_token,add_to_git_credential=True) | |
# Load the model outside of the GPU-decorated function | |
def load_model(): | |
print("Loading model...") | |
model, model_config = get_pretrained_model("stabilityai/stable-audio-open-1.0") | |
print("Model loaded successfully.") | |
return model, model_config | |
# Define the function to generate audio | |
def generate_audio(prompt, bpm, seconds_total): | |
device = "cuda" if torch.cuda.is_available() else "cpu" | |
# Download model | |
model, model_config = load_model() | |
sample_rate = model_config["sample_rate"] | |
sample_size = model_config["sample_size"] | |
model = model.to(device) | |
# Set up text and timing conditioning | |
conditioning = [{ | |
"prompt": f"{bpm} BPM {prompt}", | |
"seconds_start": 0, | |
"seconds_total": seconds_total | |
}] | |
# Generate stereo audio | |
output = generate_diffusion_cond( | |
model, | |
steps=100, | |
cfg_scale=7, | |
conditioning=conditioning, | |
sample_size=sample_size, | |
sigma_min=0.3, | |
sigma_max=500, | |
sampler_type="dpmpp-3m-sde", | |
device=device | |
) | |
# Rearrange audio batch to a single sequence | |
output = rearrange(output, "b d n -> d (b n)") | |
# Peak normalize, clip, convert to int16, and save to file | |
output = output.to(torch.float32).div(torch.max(torch.abs(output))).clamp(-1, 1).mul(32767).to(torch.int16).cpu() | |
output_path = "output.wav" | |
torchaudio.save(output_path, output, sample_rate) | |
return output_path | |
# Define the Gradio interface | |
iface = gr.Interface( | |
fn=generate_audio, | |
inputs=[ | |
gr.Textbox(label="Prompt", placeholder="Enter the description of the audio (e.g., tech house drum loop)"), | |
gr.Number(label="BPM", value=128), | |
gr.Number(label="Duration (seconds)", value=30) | |
], | |
outputs=gr.Audio(label="Generated Audio"), | |
title="Stable Audio Generation", | |
description="Generate audio based on a text prompt using stable audio tools.", | |
) | |
# Launch the interface | |
iface.launch() | |