Create README.md

README.md

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+---
+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)
+```