๐ In this video, youโll learn how to use the Qwen 3.5 model with Hugging Face API and build a real AI application using Python โ completely FREE.
If you are learning Generative AI, LLM APIs, or AI application development, Hugging Face provides access to powerful open-source models like Qwen 3.5 that can be used through a free API token.
In this step-by-step tutorial, I will show you how to:
โ Generate a Hugging Face API token (free API key)
โ Access Qwen 3.5 models via Hugging Face API
โ Connect the model with Python
โ Build a Streamlit AI application
โ Monitor token usage and responses
By the end of this video, you will have a working AI application powered by the Qwen 3.5 LLM model using Hugging Face API.
This tutorial is perfect for AI engineers, data scientists, Python developers, and anyone learning Generative AI.
โฑ Chapters
00:00 Intro โ Free API Key Series (Part 3)
00:40 Create Hugging Face API Token
01:40 Explore Qwen 3.5 Model on Hugging Face
02:30 Setup Project Folder in VS Code
03:20 Create Python Virtual Environment
04:40 Install Dependencies (requirements.txt)
06:00 Setup .env File (API Token + Model)
07:10 Create Jupyter Notebook Test
09:10 Load Environment Variables
10:00 Connect to Hugging Face API
11:30 Generate Text Using Qwen 3.5
12:10 Monitor Token Usage
12:40 Build AI Application
13:20 Run Streamlit App
13:45 Final Demo
๐ง What You Will Learn
โข How to use Qwen 3.5 model for free
โข How to create a Hugging Face API token
โข Integrate Hugging Face API with Python
โข Build AI apps using LLM models
โข Create a Streamlit AI application
โข Monitor LLM token usage
๐ Tools & Technologies
Hugging Face API
Qwen 3.5 Model
Python
Streamlit
VS Code
Jupyter Notebook
Environment Variables
๐จโ๐ป Recommended For
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โข Data Scientists
โข Machine Learning Engineers
โข Python Developers
โข Generative AI learners
โข Developers building AI applications
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