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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 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 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 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.
Learn to build a conversational agent using LangChain and GPT-3.5, leveraging vector search retrieval to provide context from Lex Fridman's podcast for intelligent responses.
Explore multilingual semantic search using Cohere's new model, comparing it with OpenAI's GPT 3.5. Learn implementation, data preparation, vector indexing, and query techniques for enhanced search capabilities.
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.
Learn to enhance LLM accuracy using retrieval augmentation in LangChain. Explore data preprocessing, embedding creation, vector database setup, and generative question-answering with citations for improved AI responses.
Explore Pinecone's hybrid search, combining vector and traditional methods for improved relevance and adaptability in semantic search and information retrieval.
Explore OpenAI's CLIP model for flexible computer vision classification without retraining, enabling generalization to new classes and images beyond initial training data.
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