What are Embeddings? Convert Chunks into Vectors | RAG Tutorial (Beginner Friendly) Hindi me

In this video, you will learn what embeddings are and how a text chunk is converted into a vector (a list of numbers) that an AI model can understand. This is the step that comes after chunking in a RAG (Retrieval-Augmented Generation) pipeline. We also write the code in Python, using the free all-MiniLM-L6-v2 model from Sentence Transformers. No API key needed. 📌 What you will learn: What is an embedding and what is a vector Who decides the dimension, and how 1D vs 2D arrays: shape (384,) vs (1, 384) How to run the model locally with sentence-transformers 💻 Code: pip install sentence-transformers from sentence_transformers import SentenceTransformer model = SentenceTransformer("all-MiniLM-L6-v2") vectors = model.encode(["Regular exercise improves heart health."]) print(vectors.shape) # (1, 384) 🔔 Next video: Vector Databases and building a RAG pipeline. #embeddings #rag #python #machinelearning #sentencetransformers #nlp #generativeai