reach-vb HF staff jbraha commited on
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4c8334b
1 Parent(s): 04b7441

Some typos in README (#26)

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- Some typos in README (3e02990f9775c87efd8f8af10faa8bf78294b338)


Co-authored-by: Joe Braha <jbraha@users.noreply.huggingface.co>

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  1. README.md +2 -2
README.md CHANGED
@@ -71,7 +71,7 @@ synthesiser = pipeline("text-to-audio", "facebook/musicgen-small")
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  music = synthesiser("lo-fi music with a soothing melody", forward_params={"do_sample": True})
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- scipy.io.wavfile.write("musicgen_out.wav", rate=music["sampling_rate"], music=audio["audio"])
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  ```
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  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
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  2. Make sure to have [`ffmpeg`](https://ffmpeg.org/download.html) installed:
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  ```
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- apt get install ffmpeg
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  ```
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  3. Run the following Python code:
 
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  music = synthesiser("lo-fi music with a soothing melody", forward_params={"do_sample": True})
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+ scipy.io.wavfile.write("musicgen_out.wav", rate=music["sampling_rate"], data=music["audio"])
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  ```
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  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.
 
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  2. Make sure to have [`ffmpeg`](https://ffmpeg.org/download.html) installed:
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  ```
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+ apt-get install ffmpeg
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  ```
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  3. Run the following Python code: