--- pipeline_tag: text-to-audio library_name: audiocraft language: en tags: - text-to-audio - musicgen - songstarter license: cc-by-nc-4.0 --- # Model Card for musicgen-songstarter-v0.2 musicgen-songstarter-v0.2 is a [`musicgen-stereo-melody-large`](https://huggingface.co/facebook/musicgen-stereo-melody-large) fine-tuned on a dataset of melody loops from my Splice sample library. It's intended to be used to generate song ideas that are useful for music producers. It generates stereo audio in 32khz. ## Usage Install [audiocraft](https://github.com/facebookresearch/audiocraft): ``` pip install -U git+https://github.com/facebookresearch/audiocraft#egg=audiocraft ``` Then, you should be able to load this model just like any other musicgen checkpoint here on the Hub: ```python import torchaudio from audiocraft.models import MusicGen from audiocraft.data.audio import audio_write model = MusicGen.get_pretrained('nateraw/musicgen-songstarter-v0.2') model.set_generation_params(duration=8) # generate 8 seconds. wav = model.generate_unconditional(4) # generates 4 unconditional audio samples descriptions = ['acoustic, guitar, melody, trap, d minor, 90 bpm'] * 3 wav = model.generate(descriptions) # generates 3 samples. melody, sr = torchaudio.load('./assets/bach.mp3') # generates using the melody from the given audio and the provided descriptions. wav = model.generate_with_chroma(descriptions, melody[None].expand(3, -1, -1), sr) for idx, one_wav in enumerate(wav): # Will save under {idx}.wav, with loudness normalization at -14 db LUFS. audio_write(f'{idx}', one_wav.cpu(), model.sample_rate, strategy="loudness", loudness_compressor=True) ``` ## Samples