Spaces:
Runtime error
Runtime error
File size: 2,074 Bytes
3c26e4b 91a1e69 3c26e4b 16e998b 91a1e69 7e248e7 3c26e4b 91a1e69 3c26e4b 91a1e69 3c26e4b 91a1e69 3c26e4b 16e998b 3c26e4b 06f6a07 05ebe3d 06f6a07 3c26e4b 91a1e69 3c26e4b 06f6a07 3c26e4b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 |
from transformers import MusicgenForConditionalGeneration, AutoProcessor, set_seed
import torch
import numpy as np
import gradio as gr
model = MusicgenForConditionalGeneration.from_pretrained("facebook/musicgen-small")
processor = AutoProcessor.from_pretrained("facebook/musicgen-small")
device = "cuda:0"
model.to(device)
sampling_rate = model.audio_encoder.config.sampling_rate
frame_rate = model.audio_encoder.config.frame_rate
text_encoder = model.get_text_encoder()
def generate_audio(prompt, negative_prompt, guidance_scale=3, audio_length_in_s=20, seed=0):
inputs = processor(
text=[prompt, negative_prompt],
padding=True,
return_tensors="pt",
).to(device)
with torch.no_grad():
encoder_outputs = text_encoder(**inputs)
max_new_tokens = int(frame_rate * audio_length_in_s)
set_seed(seed)
audio_values = model.generate(inputs.input_ids[0][None, :], attention_mask=inputs.attention_mask, encoder_outputs=encoder_outputs, do_sample=True, guidance_scale=guidance_scale, max_new_tokens=max_new_tokens)
audio_values = (audio_values.cpu().numpy() * 32767).astype(np.int16)
return (sampling_rate, audio_values)
EXAMPLES = [
["80s pop track with synth and instrumentals", "drums", 1.01, 15, 0],
["80s pop track with synth and instrumentals", "drums", 3, 15, 0],
["80s pop track with synth and instrumentals", "drums", 5, 15, 0],
["80s pop track with synth and instrumentals", "drums", 7, 15, 0],
["80s pop track with synth and instrumentals", "drums", 10, 15, 0],
]
gr.Interface(
fn=generate_audio,
inputs=[
gr.Text(label="Prompt", value="80s pop track with synth and instrumentals"),
gr.Text(label="Negative prompt", value="drums"),
gr.Slider(1.5, 10, value=3, step=0.5, label="Guidance scale"),
gr.Slider(5, 30, value=15, step=5, label="Audio length in s"),
gr.Slider(0, 10, value=0, step=1, label="Seed"),
],
outputs=[
gr.Audio(label="Generated Music", type="numpy"),
],
examples=EXAMPLES,
).launch()
|