Open Source LLMs with ChatGPT Practice Exam
Open Source LLMs with ChatGPT Practice Exam
The Open Source LLMs with ChatGPT Exam is an advanced evaluation tailored for individuals who want to master the use of large language models (LLMs) locally and privately. This exam covers no-code and low-code solutions for running open-source LLMs, advanced Python techniques for API integrations, and building web interfaces. With a hands-on focus, the exam ensures you understand both the technical implementation and real-world applications of LLMs. By completing this exam, you'll validate your ability to operate LLMs locally, build custom APIs, and unlock the full potential of these transformative tools.
Skills Evaluated
This exam is designed to assess your proficiency in operating and integrating open-source LLMs, such as Google’s Gemma:7b and Llama3, along with the official OpenAI API. From setting up local environments to advanced usage, the exam evaluates your skills in:
- Running no-code LLMs locally for privacy and cost-free applications.
- Implementing low-code solutions using Python for streaming ChatGPT responses.
- Leveraging Python APIs for integrating OpenAI and open-source models.
- Exploring function calling within ChatGPT models for advanced tasks.
- Using Llama3 with Python to create web interfaces for practical applications.
Who should take this Exam?
This exam is ideal for:
- AI Enthusiasts: Individuals keen on operating LLMs locally and privately, without relying on the cloud.
- Beginners to Low-Code Practitioners: Those exploring no-code or minimal-code solutions for leveraging LLMs.
- Python Developers: Professionals seeking to integrate LLMs into workflows or applications.
- Budget-Conscious Learners: Those interested in using LLMs completely free of charge.
Knowledge Gained
- Local LLM Operations: Configure and run open-source LLMs locally, including server API endpoints.
- API Integrations: Integrate OpenAI API and explore Python-based API calls for open-source LLMs.
- Streaming Responses: Implement low-code solutions for fetching responses in batch and streaming modes.
- Function Calling: Learn to use function-calling features with ChatGPT models in Python.
- Llama3 and Web Interfaces: Operate Llama3 models and develop Python-based web frontends.
- Streamlit Web Frontends: Build simple web applications to interact with LLM APIs.
- Experimentation: Explore various open-source models to understand their capabilities and limitations.
Topics Covered
The Open Source LLMs with ChatGPT Exam covers the following topics -
Domain 1. Setting Up and Exploring Local LLMs (Free Chapter)
- Downloading required software and setting up local environments.
- Running open-source models without code locally through the command line.
- Exploring local server API endpoints for no-code and Python integrations.
Domain 2. Advanced Usage and API Integrations
- Streaming responses from open-source LLMs using Python.
- Implementing OpenAI API calls with low-code solutions.
- Function calling with ChatGPT models for advanced integration.
- Operating Llama3 models with Python for web applications.
- Building web frontends with Streamlit for streaming LLM APIs.
Key Benefits
- Cost Efficiency: Use open-source LLMs for free, eliminating reliance on cloud solutions.
- Privacy: Run LLMs locally to ensure complete control over your data.
- Accessibility: No prior coding experience? No problem! The exam includes no-code and low-code solutions.
- Hands-On Learning: Gain practical experience with Python, API integrations, and web application development.
- Real-World Applications: Learn to apply LLMs for personal, professional, and business use cases.
- Skill Validation: Showcase your expertise in one of the most sought-after AI domains.
