{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/55de8ffa5d624b8fb37220dba90f9a10\" frameborder=\"0\" width=\"1920\" height=\"1440\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1440,"width":1920,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1440,"thumbnail_width":1920,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/55de8ffa5d624b8fb37220dba90f9a10-cc49f0ab5cff8438.gif","duration":308.279,"title":"Create Sentiment Model API","description":"In this video, I walk you through the process of setting up an API for a sentiment analysis model. We’ll create the necessary files, including main.py, schemas.py, and sentiment.py, and I’ll show you how to implement the predict function to return sentiment scores. I also demonstrate how to run the service and test it using a sample input. Please make sure to follow along and set up the API as discussed."}