Posted by admin

\ud83d\udc4bHello my dear coders, In this video, I'll demonstrate how to connect with your data using LangChain for nothing at all, without the requirement for OpenAI apis. Huggingface hub embeddings will be used to convert our documents into vector representations (embeddings). We will once more use open-sourced models (such as - flan T5) in place of OpenAI models for large language models. With LangChain, every step will be completed using FREE & open source technologies. \ud83d\udc490:00 Intro about the embedding and model. \ud83d\udc491:30 Installling Dependency. \ud83d\udc492:00 Importing the modules. \ud83d\udc492:30 Processing Url, Loading Embedding and Semantic Search. \ud83d\udc499:10 Loading The Model and Inference. \u270d\ufe0fLearn and write the code along with me. \ud83d\ude4fThe hand promises that if you subscribe to the channel and like this video, it will release more tutorial videos. \ud83d\udc50I look forward to seeing you in future videos Colab : https://colab.research.google.com/drive/1UHUnnLITV07X09JEYTK7tEQutyGLtZoY#scrollTo=16SUG_DEASNt #langchiantutorial langchian chatbot langchain hugging face langchian opensource langchain agent langchain demo langchain Information reterival huggingface langchain llama langchain google flant5 langchain ai langchain langchain tutorial build question answering system #LangChain #Pinecone #GPT4 #ChatGPT #SemanticSearch #DocumentQnA"