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Building and Training Your Own SLM

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Creating an independent Small Language Model (SLM) is a rewarding project that bridges the gap between deep learning theory and practical, local application. By keeping your model local, you retain full control over your data and system architecture. Below is a structured approach to building and training your own model from the ground up on a local Ubuntu environment. Before you begin, ensure your development environment is optimized for local computation. A robust setup with a capable GPU (such as an NVIDIA RTX series) and sufficient RAM is recommended for efficient training. Use Ubuntu for a stable, customizable development environment. Verify your environment with the following commands:    * Update your package lists:  sudo apt update.    * Install pip:  sudo apt install python3-pip    *I nstall necessary libraries:  pip install torch tiktoken An SLM relies on the quality of its input data. For a personal AI, curated, factual...
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Viper4android 2.7.2.1 on Android 12

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You need the following Magisk modules:

1. Ainur Narsil - a library for audio modification
2. Viper4android 2.7.2.1 - an audio modification tool

To obtain these modules, use this app.

After installing all the modules, follow these steps:

1. Start Viper4android and your music player.
2. Disable the audio modification library in Magisk.
3. Reboot your phone.
4. Open Viper4android and reinstall the driver.
5. Once your phone finishes booting, start Viper4android again.
6. Toggle on the audio modification library and reboot your phone.
7. Install the driver once more and then reboot.

That's it!

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