In this video, I dive into Alibaba's latest Qwen-2 model, the best open weight model available. We explore function calling and agentic workflows using Qwen-2's powerful features. The model family ranges from 0.5 billion to 72 billion parameters, with support for up to 128,000 tokens and multiple languages, including Middle Eastern and Southeastern languages. I'll show you how to perform function calling and create custom agents with the Qwen-2 agent framework.

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INSTRUCTION:
conda create -n qwen python=3.10
conda activate qwen

LINKS:
Qwen-2: https://qwenlm.github.io/blog/qwen2/
Qwen-Agent: https://github.com/QwenLM/Qwen-Agent
Function Calling Example: https://qwen.readthedocs.io/en/latest...
Agent Usage Example: https://qwen.readthedocs.io/en/latest...
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TIMESTAMPS:
00:00 Introduction to Quen2 Models
01:51 Difference between function calling and Agents
04:31 Setting Up and Running Quen2 Locally
07:31 Function Calling with Quen2: A Practical Example
11:54 Creating Custom Agents with Quen2
17:04 Impact of Quantization on Model Performance


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