Скачать или смотреть SIMPLE AI TUTORIAL - THE MOST SIMPLE WAY FOR GPT 3 5 TURBO INSTRUCT

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Today, we're diving into a tutorial from the "Simple AI Tutorial" channel. This tutorial is helpful to demystify AI programming, making it more accessible and understandable.

Colabs: First, let's touch on Colabs. Colabs, or Google Colaboratory, is a free cloud-based platform by Google.

If you have a Google Account, you can use it for free and store and run your Colab files on Google Drive.

It's a space where you can write and execute Python code directly in your web browser.

You can install components and run programs without having to install Python or configure virtual environments.

It's like having a fast Python installation in the cloud, and the best part? It offers free GPU access, which is a boon for machine learning tasks.

Installing Required Components: We begin by installing two essential components: open ai and langchain. The open ai package is our gateway to interact with the Open AI API. On the other hand, langchain is a framework designed for developing applications powered by AI language models. It allows these applications to connect with other data sources and interact with their environment.

Importing Modules: Next, we import two modules:

The Open AI module from langchain.llms. This module will enable us to utilize the capabilities of the Open AI language models.

Then we import the os module, which provides a way of interacting with the operating system, especially when dealing with environment variables.

Setting Up the API Key: For the Open AI API to work, it requires an API key. This key is set as an environment variable using the os module. Remember, always keep your API keys private!

Defining the AI Model: Here, we initialize the language model from Open AI. That is the inventor of Chat GPT and you can get free API keys on Open ai.com. We're using the new 'gpt-3.5-turbo-instruct' model with a temperature setting of 0. The temperature affects the randomness of the model's output. A value of 0 makes the output deterministic, while higher values make it more random. Or in other words, 0 is for facts, 1 is for story telling.

User Input: The code prompts the user to enter a question. It's designed to be bilingual, accepting questions in English and German. The prompt instructs the system to answer in the language of the question, ensuring consistency.

Generating a Response: With the user's question in hand, the code uses the predict method of the language model to generate a response. This response is based on the capabilities of the 'gpt-3.5-turbo-instruct' model.

Displaying the Result: Finally, the code prints out the AI-generated response to the user's question.

Thank you for watching this video from the Simple AI Tutorial channel. Our goal is to make AI programming more approachable, especially in the wake of the AI shock.

If you found this tutorial helpful, please subscribe and give this video a thumbs up. I'll see you in the next one!