Get a Taste of LLMs from GPT4All

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Large language models (LLMs) have gained immense popularity in recent times, with ChatGPT becoming a household name. While trying out ChatGPT online is straightforward, some users may seek an offline alternative that can be run on their computers. In this article, you will learn about GPT4All, an LLM that you can install locally. Specifically, you will discover:

  • What GPT4All is.
  • How to install the desktop client for GPT4All.
  • How to run GPT4All in Python.

Let’s get started!

Overview

This article is structured into three sections:

  1. What is GPT4All?
  2. How to Acquire GPT4All
  3. How to Use GPT4All in Python

What is GPT4All?

The term “GPT” stems from the title of a pivotal 2018 paper, “Improving Language Understanding by Generative Pre-Training,” authored by Radford et al. This paper illustrates how transformer models can effectively understand human language.

Since then, numerous attempts have been made to develop language models using this architecture, revealing that sufficiently large models can yield excellent results. However, many existing models are proprietary, often available only through paid subscriptions or with restrictive licensing terms. Some of these models are simply too large to run on standard hardware.

The GPT4All project aims to make LLMs accessible to the public on common hardware, allowing users to train and deploy their models. The project offers pre-trained models that are small enough to run efficiently on a typical CPU.

How to Acquire GPT4All

For those looking to use pre-trained models, GPT4All can be accessed from gpt4all.io, where you can run it as a desktop application or utilize a Python library. You can download the installer compatible with your operating system to set up the desktop client, which is only a few hundred MB in size. Upon installation, the application prompts you to select a model, with the “gpt4all-j-v1.3-groovy” model being a popular choice that balances size and performance.

Once the client and model are configured, you can type your messages in the input box. The model functions best with conversational inputs, generally excelling in English.

Example Interaction:
If you ask, “Give me a list of 10 colors and their RGB codes,” GPT4All should respond promptly with a structured list.

How to Use GPT4All in Python

The core component of GPT4All is the model itself. Although the desktop client serves as a user interface, you can also interact with the model via a Python library.

To install the library, use the following pip command:

pip install gpt4all

Note: This library is continually evolving, and functions may change. The following examples have been tested on version 1.0.12 but may not work in future versions.

You can use it in Python with just a few lines of code:

import pprint
import gpt4all

model = gpt4all.GPT4All("orca-mini-7b.ggmlv3.q4_0.bin")
with model.chat_session():
    response = model.generate("Give me a list of 10 colors and their RGB codes")
    print(response)
    pprint.pprint(model.current_chat_session)

When you run this code for the first time, the model file will be downloaded if not already available. Once loaded, you can provide input and receive output as a string. For instance, the output may resemble:

“Sure, here’s a list of 10 colors along with their RGB codes:

  1. Red (255, 0, 0)
  2. Blue (0, 0, 255)
  3. Green (0, 255, 0)
  4. Yellow (255, 255, 0)
  5. Orange (255, 165, 0)
  6. Purple (192, 118, 192)
  7. Pink (255, 192, 203)
  8. Maroon (153, 42, 102)
  9. Teal (0, 128, 128)
  10. Lavender (238, 102, 147)”

The chat history is stored in the model’s attribute current_chat_session as a Python list, allowing for easy reference and continuation of conversations.

Iterative Interaction Example:

questions = [
    "Can you explain what a large language model is?",
    "What are some applications of LLMs?",
    "What limitations do these models have?",
    "Summarize the above in two sentences.",
]

for question in questions:
    answer = model.generate(question)
    print("Q:", question)
    print("A:", answer)

pprint.pprint(model.current_chat_session)

In this loop, ChatGPT’s current context is maintained as you interact, creating a coherent dialogue back and forth.

Summary

GPT4All is a versatile tool that allows you to explore interactions with large language models on your computer. In this article, you learned about:

  • The desktop client for GPT4All, which is easy to install.
  • The Python interface, enabling you to interact with the model programmatically.
  • The availability of various language models for different tasks.

By leveraging GPT4All, you can gain firsthand experience with language models and appreciate their capabilities and limitations.

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