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DSXiangLi/DecryptPrompt

⭐ 3441 repository created 2023-02-10

DecryptPrompt is a comprehensive and continuously updated resource hub focused on the latest developments in large language models (LLMs), prompt engineering, and AI-generated content (AIGC) applications. The project aggregates a wide range of materials including summaries of research papers on prompts and LLMs, open-source datasets, models, and frameworks for inference, fine-tuning, and retrieval-augmented generation (RAG). It also compiles tutorials, classic blogs, and interviews from AI conferences to help users deepen their understanding of prompt techniques and LLM advancements. The repository is structured to guide users through various aspects of prompt engineering and LLM research, featuring a detailed series of blog posts that decode complex topics such as tuning-free prompts, instruction tuning, reinforcement learning with human feedback (RLHF), chain-of-thought reasoning, and agent-based LLM applications. These blog series provide in-depth analyses and practical insights into state-of-the-art methods and innovations in the field. Additionally, DecryptPrompt offers curated lists of influential papers and surveys related to in-context learning, tool learning, chain-of-thought reasoning, and evaluation benchmarks for LLMs. It highlights major pre-trained models like GLM-130B, PaLM, GPT-4, and LLaMA, providing technical reports and comparative studies to keep the community informed about foundational models and their capabilities. This project serves as a valuable knowledge base for AI researchers, practitioners, and enthusiasts who want to stay updated on prompt engineering strategies, LLM fine-tuning techniques, and the latest trends in AI content generation. By consolidating diverse resources and expert analyses, DecryptPrompt facilitates a deeper understanding of how to effectively leverage LLMs for various applications, from natural language understanding to intelligent agent design.

https://github.com/DSXiangLi/DecryptPrompt

ai-applicationsai-generated-contentai-research-papersaigcblog-serieschain-of-thoughtchain-of-thought-reasoningchatgptdatasetsdemonstrationevaluation-benchmarksfew-shot-learningfine-tuningglm-130bgpt-4in-context-learninginstruction-tuningintelligent-agentslarge-language-modelsllamallmllm-agentopen-source-modelspalmpaperspre-trained-modelspromptprompt-engineeringprompt-tuningragreinforcement-learning-with-human-feedbackretrieval-augmented-generationrlhftutorialszero-shot-learning