facebook
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musicgen-medium

Inference Endpoints

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reach-vb HF staff commited on Nov 17, 2023

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1 Parent(s): ecb62cc

Update README.md (#9)

- Update README.md (fe86836c0b933dc24bd5a53e33483eb5696650cf)

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@@ -71,7 +71,7 @@ synthesiser = pipeline("text-to-audio", "facebook/musicgen-medium")
 music = synthesiser("lo-fi music with a soothing melody", forward_params={"do_sample": True})
-scipy.io.wavfile.write("musicgen_out.wav", rate=music["sampling_rate"], music=audio["audio"])
 ```
 3. Run inference via the Transformers modelling code. You can use the processor + generate code to convert text into a mono 32 kHz audio waveform for more fine-grained control.
@@ -122,7 +122,7 @@ pip install git+https://github.com/facebookresearch/audiocraft.git
 2. Make sure to have [`ffmpeg`](https://ffmpeg.org/download.html) installed:
 ```
-apt get install ffmpeg
 ```
 3. Run the following Python code:

 music = synthesiser("lo-fi music with a soothing melody", forward_params={"do_sample": True})
+scipy.io.wavfile.write("musicgen_out.wav", rate=music["sampling_rate"], data=music["audio"])
 ```
 3. Run inference via the Transformers modelling code. You can use the processor + generate code to convert text into a mono 32 kHz audio waveform for more fine-grained control.
 2. Make sure to have [`ffmpeg`](https://ffmpeg.org/download.html) installed:
 ```
+apt-get install ffmpeg
 ```
 3. Run the following Python code: