ardianfe / stable-audio-prod

cerate music with open source

  • Public
  • 68.7K runs
  • L40S
  • GitHub
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Input

string
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A description of the music you want to generate.

file

An audio file that will influence the generated music. If `continuation` is `True`, the generated music will be a continuation of the audio file. Otherwise, the generated music will mimic the audio file's melody.

integer

Duration of the generated audio in seconds.

Default: 8

boolean

If `True`, generated music will continue `melody`. Otherwise, generated music will mimic `audio_input`'s melody.

Default: false

integer
(minimum: 0)

Start time of the audio file to use for continuation.

Default: 0

integer
(minimum: 0)

End time of the audio file to use for continuation. If -1 or None, will default to the end of the audio clip.

boolean

If `True`, the EnCodec tokens will be decoded with MultiBand Diffusion. Only works with non-stereo models.

Default: false

string

Strategy for normalizing audio.

Default: "loudness"

integer

Reduces sampling to the k most likely tokens.

Default: 250

number

Reduces sampling to tokens with cumulative probability of p. When set to `0` (default), top_k sampling is used.

Default: 0

number

Controls the 'conservativeness' of the sampling process. Higher temperature means more diversity.

Default: 1

integer

Increases the influence of inputs on the output. Higher values produce lower-varience outputs that adhere more closely to inputs.

Default: 3

string

Output format for generated audio.

Default: "mp3"

integer

Seed for random number generator. If None or -1, a random seed will be used.

*integer

song id to store to GCS

*string
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key password

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Output

{ "output": "https://storage.googleapis.com/lagoe_prod_generated_songs/20001/20001.mp3" }
Generated in
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This output was created using a different version of the model, ardianfe/stable-audio-prod:0271bd81.

Run time and cost

This model runs on Nvidia L40S GPU hardware. We don't yet have enough runs of this model to provide performance information.

Readme

We fine tuned meta music gen with additional data set