Mehmet Egemen Pembe

Success Stories


Offline AI Model Deployment Project

Exploring AI capabilities without the cloud: running powerful language models entirely offline on local devices.

Offline AI

Overview:

Have you ever imagined running a ChatGPT-like AI model completely on your computer or phone, without the internet? I explored this concept by testing open-source applications that support offline AI deployments — showcasing what's possible today with the right tools and models.

Challenges:

  • Ensuring smooth AI model execution on resource-constrained devices
  • Navigating hardware limitations (CPU, RAM, storage) for offline performance
  • Maintaining privacy and speed without sacrificing model quality
  • Solution:

    I tested two open-source tools. Both apps utilize models from Hugging Face, a platform for discovering and running AI models offline.

  • Jan — a cross-platform app for running Hugging Face models offline on desktop
  • PocketPal — a mobile-ready offline AI app for Android and iOS
  • Models Tested:

  • Gemma-2-2B (by Google): Flexible and powerful for general tasks
  • LLaMA-3.2-3B (by Meta): Optimized for fast and accurate responses on local environments
  • Results:

  • Achieved full conversational capability offline with no lag
  • Verified local performance and model accuracy without cloud dependency
  • Demonstrated clear advantages in privacy, speed, and accessibility

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