Private GPT: Run Open-Source Language Models Locally

Discover Private GPT, a powerful open-source project that brings together open-source embedding models and large language models. With over 15,000 stars on GitHub, this trending tool allows you to run language models locally without an internet connection, ensuring complete privacy throughout the process.

Key Features of Private GPT

  • Combines open-source embedding models with large language models
  • Enables local execution without internet connectivity
  • Follows a Blank Chain with GPT for all approach and utilizes Nama CPP embeddings

Setting up Private GPT

Setting up Private GPT is a straightforward process. Make sure you have Python 3.10 or a later version installed on your computer. While Git is recommended for download, you can also opt for the zip file.

All the necessary models, including the large language model and corresponding embeddings, are provided within the project. To get started, follow these steps:

  1. Clone the GitHub repository
  2. Create a new folder named "models"
  3. Copy the downloaded models into the "models" folder
  4. Rename the example.env file to .env
  5. Update the model path in the .env file to the absolute path for the embedding model binary

By following these steps, you'll have Private GPT set up and ready to run on your local machine.


Q: What is Private GPT?

A: Private GPT is an open-source project that combines open-source embedding models with large language models, allowing local execution without an internet connection.

Q: How can I set up Private GPT?

A: To set up Private GPT, clone the GitHub repository, create a "models" folder, copy the downloaded models, rename the example.env file to .env, and update the model path in the .env file.

Q: What are the key features of Private GPT?

A: Private GPT combines open-source embedding models with large language models, supports local execution, and utilizes Blank Chain with GPT for all and Nama CPP embeddings.

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