Google Music Language Model (LM) is a state-of-the-art deep learning model for music generation. This model has been trained on a massive dataset of MIDI files and can generate new music compositions in various styles, tempos, and genres. Access to Google Music LM can be valuable for musicians, composers, and music enthusiasts who want to explore new musical ideas, generate new compositions, or study the structure and patterns of music.

In this article, we will show you how to get access to Google Music LM and how to use it for music generation.



Prerequisites

Before we get started, you will need the following:

  1. A Google Cloud Platform (GCP) account: If you don't already have one, you can sign up for a free account here: https://cloud.google.com/
  2. Access to the Google Cloud AI Platform: This service is not enabled by default in your GCP project. To enable it, you will need to go to the Google Cloud Console, select your project, and navigate to the AI Platform section.
  3. A billing account: To use Google Music LM, you will need to have a billing account associated with your GCP project.
  4. Familiarity with the Google Cloud Console: You should have a basic understanding of how to use the Google Cloud Console and how to navigate the various sections of the console.

Step 1: Create a new model in the AI Platform

The first step to accessing Google Music LM is to create a new model in the AI Platform. Here are the steps to create a new model:

  1. Go to the Google Cloud Console (https://console.cloud.google.com/).
  2. Select your project.
  3. Go to the AI Platform section and select the "Models" tab.
  4. Click the "Create model" button.
  5. In the "Create model" form, give your model a name, select the "Music Transformer" model from the list of pre-trained models, and select your GCP region.
  6. Click the "Create" button to create the model.

Step 2: Deploy the model

Once you have created the model, you will need to deploy it in order to make it accessible for inference. Here are the steps to deploy the model:

  1. In the "Models" tab of the AI Platform, select the model you just created.
  2. Go to the "Versions" tab and click the "Create version" button.
  3. In the "Create version" form, give your version a name, select the "Music Transformer" image, and select the hardware accelerator you want to use for inference (e.g., GPU, TPU).
  4. Click the "Create" button to create the version.

Step 3: Use the model for music generation

Once you have deployed the model, you can use it to generate music compositions. There are several ways to use the model, including using the AI Platform API, using the AI Platform client libraries, or using a Jupyter notebook in the AI Platform Notebooks service.

Here, we will show you how to use the AI Platform API to generate music compositions:

  1. Obtain an API key: You will need to obtain an API key in order to use the API. To obtain an API key, go to the Google Cloud Console, select your project, and navigate to the API & Services section.
  2. Make an API request: To make an API request, you will need to send a POST request to the API endpoint for the model with the desired parameters, including the API key, the model version
About Google MusicLM

Google Music LM can generate music compositions based on text inputs, such as chord sequences or lyrics. To generate music using text inputs, you will need to encode the text into a format that the model can understand and then pass the encoded input to the model as part of the inference request.

The encoding process can involve converting the text input into a sequence of musical symbols, such as notes, chords, or lyrics. The specific encoding method will depend on the type of input and the desired output format. For example, if you are encoding chord sequences, you might use a simple numerical representation of the chords, such as "1" for C major, "2" for D minor, etc. If you are encoding lyrics, you might use a word-level encoding, where each word is represented by a unique symbol.

Once you have encoded your text input, you can pass it to the model as part of the inference request. The model will then generate a musical composition based on the encoded input. You can specify various parameters for the model, such as the desired tempo, genre, or style, to control the output of the model.

Here's an example of how you can generate music using text inputs with Google Music LM:

  • Encode your text input into a sequence of musical symbols.
  • Pass the encoded input to the model as part of the inference request, along with any desired parameters.
  • The model will generate a musical composition based on the encoded input and the specified parameters.
  • Decode the output of the model into a musical score or MIDI file.
Note that this is a simplified overview of the process, and the actual implementation can be more complex, depending on the desired output format and the encoding method used. To learn more about generating music with Google Music LM and text inputs, you may refer to the Google AI Platform documentation or explore the code examples provided by Google or the open-source community.