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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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Update drivers - Lumia WoA

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only for Lumia 950 and 950XL devices running Windows10 on Arm


Right-click on the Driver Updater zip file, extract it and put it in C:\  and the driver's zip in C:\UpdatedDrivers\Lumia-Drivers-Full

Put the phone in mass storage mode and plug it into a Windows PC 

 open a PowerShell window as administrator in the driver updater folder

For Lumia 950: type or copy and paste the following 
(Assuming the windows partition is J:) 

.\DriverUpdater.exe C:\UpdatedDrivers\Lumia-Drivers-Full\definitions\Desktop\ARM64\Internal\950.txt C:\UpdatedDrivers\Lumia-Drivers-Full\ J:\

For Lumia 950XL 

.\DriverUpdater.exe C:\UpdatedDrivers\Lumia-Drivers-Full\definitions\Desktop\ARM64\Internal\950xl.txt C:\UpdatedDrivers\Lumia-Drivers-Full\ J:\


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