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const axios = require('axios');
const api_key = "YOUR API-KEY";
const url = "https://api.segmind.com/v1/meta-musicgen-medium";
const data = {
"prompt": "lo-fi music with a soothing melody",
"duration": 10,
"seed": 42
};
(async function() {
try {
const response = await axios.post(url, data, { headers: { 'x-api-key': api_key } });
console.log(response.data);
} catch (error) {
console.error('Error:', error.response.data);
}
})();Attributes
prompt to generate music
duration of the audio
min : 1,
max : 30
Seed for audio generation.
min : -1,
max : 9999
To keep track of your credit usage, you can inspect the response headers of each API call. The x-remaining-credits property will indicate the number of remaining credits in your account. Ensure you monitor this value to avoid any disruptions in your API usage.
MusicGen: Transforming Text into Music
MusicGen by Meta is an advanced text-to-music model designed to generate high-quality music samples from text descriptions or audio prompts. Leveraging a single-stage auto-regressive Transformer architecture, MusicGen is trained on a 32kHz EnCodec tokenizer with four codebooks sampled at 50 Hz. This innovative approach allows for efficient and high-fidelity music generation.
Key Features of MusicGen
-
Text-to-Music Generation: Converts textual descriptions into diverse and high-quality music samples.
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Auto-Regressive Transformer: Utilizes a single-stage auto-regressive Transformer model for seamless music generation.
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Efficient Training: Trained on a 32kHz EnCodec tokenizer with four codebooks, enabling efficient processing and high-quality output.
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Parallel Prediction: Introduces a small delay between codebooks, allowing parallel prediction and reducing the number of auto-regressive steps to 50 per second of audio.
Use cases
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Music Production: Generate unique music tracks based on textual descriptions for use in various media.
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Creative Projects: Enhance creative projects with custom-generated music that matches specific themes or moods.
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Interactive Experiences: Integrate into interactive applications to provide dynamic and responsive musical experiences.
Popular Models
