Examples for quickly getting started using Deep Lake! https://activeloop.ai/
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Updated
May 17, 2023 - Jupyter Notebook
Examples for quickly getting started using Deep Lake! https://activeloop.ai/
This is a CLI app using LangChain and Activeloop vector DB to index and chat with the Chainstack docs
Intelligent sales assistant built using Deep Lake, Whisper, LangChain, and GPT 3.5/4
ActiveLoop's Course on LangChain and Vector Databases in Production
LLMs are deep learning models with billions of parameters that excel at a wide range of natural language processing tasks. They can perform tasks like translation, sentiment analysis, and chatbot conversations without being specifically trained for them
An example Airflow Pipeline with Deeplake for Machine Learning
Chatbot assistant enabling GitHub repository interaction using LLMs with Retrieval Augmented Generation
A list of examples for different use of LangChain
A Statistical Research GPT that integrates DeepLake and Eurostat API
RAG project for QA retrieval using Llama Index
This Python code retrieves an article from a provided URL, extracts its title and text, and then utilizes the ChatOpenAI library (assuming access) to generate a bulleted summary using the GPT-4 model.
Artificial Intelligence LLM experiments and quick intros using Ollama, GPT4All, OpenAI and HuggingFace models with LangChain and DeepLake vector store
DrakeLLM is developed to help students to solve the issue of making notes from videos, books and others. Utilising RAG, Drake helps in making quick notes along with a Q&A bot. Books, YouTube tutorials or Videos, Drake supports all your means.
Unlock the potential of AI-driven solutions and delve into the world of Large Language Models. Explore cutting-edge concepts, real-world applications, and best practices to build powerful systems with these state-of-the-art models.
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