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Learn effective prompt engineering techniques for GPT-3 and other LLMs. Explore anatomy, temperature, few-shot training, external information, and context windows to enhance AI-generated outputs.
Introduction to LangChain framework for building apps with large language models, comparing GPT-3 and open-source alternatives, and exploring key components for advanced NLP applications.
Explore chatbot memory implementation in LangChain, including Conversation Chain, Summary Memory, and Buffer Window Memory. Learn to enhance AI conversations with context retention.
Learn to create a chatbot and conversational agent using Falcon 40B, the top open-source LLM, with Hugging Face Transformers and LangChain. Explore code generation, refactoring, and agent capabilities.
Learn to build a generative question-answering system using open-source AI and Python. Covers architecture, data preprocessing, embedding, indexing, and querying with BART for multi-sentence answers to open-ended questions.
Learn to enhance Llama 2 using Retrieval Augmented Generation (RAG). Build a pipeline with Pinecone, Llama 2 13B, and integrate it using Hugging Face and LangChain for improved, up-to-date language model performance.
Learn to interact with web APIs using Python, covering essentials like JSON, requests, and real-world examples with Google Geocoding and GitHub APIs.
Enhance GPT-4's capabilities with retrieval augmentation, using Pinecone vector database to provide up-to-date information and reduce hallucinations in AI-generated responses.
Explore rerankers in retrieval pipelines, comparing them to embedding retrieval setups. Learn to implement reranking with Cohere AI and OpenAI models, optimizing accuracy in RAG systems.
Explore Canopy, a new RAG framework for easy top-tier performance. Learn setup, data input, upserting, CLI chatting, and complex query handling. Compare RAG to LLM-only approaches.
Explore MPT-7B LLM implementation in Hugging Face and LangChain, covering setup, initialization, tokenization, and text generation. Learn to leverage open-source models for AI applications.
Explore Hugging Face's new LLM Agents: easy-to-use, multi-modal AI tools integrated with HF's vast model hub. Learn implementation, querying, and potential applications in this comprehensive overview.
Learn to create powerful conversational agents using vector databases and LangChain, combining retrieval augmentation with chatbots for enhanced data freshness and domain-specific knowledge.
Explore OpenAI's new function calling feature for GPT-4 and GPT-3.5-turbo, enabling chatbots to utilize programming functions as tools. Learn implementation, creation, and practical applications in this tutorial.
Learn to build a sophisticated chatbot agent using OpenAI's Function Calling, featuring conversational memory, internal thoughts, and tool usage capabilities for GPT-4 and GPT-3.5-Turbo.
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