Apple(US:AAPL) Mediumยท2025-10-11 12:39Core Insights - The article provides a comprehensive guide on deploying an AI application using HuggingFace models, detailing each step from account creation to live deployment. Group 1: Account Setup - Users are instructed to create a HuggingFace account and generate an access token, which is essential for accessing models and tracking usage [2][3][4]. Group 2: Google Colab Setup - The guide explains how to set up Google Colab with the HuggingFace token, emphasizing the importance of secure token storage and the benefits of using Colab for GPU access [5][6][7]. Group 3: Model Interaction - Users are introduced to ten different AI models, showcasing their capabilities in tasks such as sentiment analysis, zero-shot classification, named entity recognition, and more [8][9][10][11][12][13][14]. Group 4: Application Development - The article outlines the process of creating a Streamlit application for real-time sentiment analysis, highlighting the ease of deployment and user interaction [15][16]. Group 5: GitHub Repository Creation - Instructions are provided for creating a GitHub repository to host the application, emphasizing the importance of version control and deployment source management [17][18][19]. Group 6: Application Files - The necessary files for the application are detailed, including the main application file, requirements file, and optional secrets configuration for secure token management [20][21][22][24]. Group 7: Deployment Process - The deployment process to Streamlit Cloud is explained, including steps for linking the GitHub repository and managing secrets for secure access [25][26]. Group 8: Application Testing - Users are encouraged to test the live application with various text samples to demonstrate its functionality and effectiveness in sentiment analysis [26][27].