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Prompt Engineering Guide | Prompt Engineering Guide #314

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irthomasthomas opened this issue Jan 8, 2024 · 0 comments
Open
1 task

Prompt Engineering Guide | Prompt Engineering Guide #314

irthomasthomas opened this issue Jan 8, 2024 · 0 comments
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AI-Agents Autonomous AI agents using LLMs embeddings vector embeddings and related tools finetuning Tools for finetuning of LLMs e.g. SFT or RLHF llm Large Language Models llm-evaluation Evaluating Large Language Models performance and behavior through human-written evaluation sets llm-experiments experiments with large language models llm-inference-engines Software to run inference on large language models Models LLM and ML model repos and links prompt-engineering Developing and optimizing prompts to efficiently use language models for various applications and re RAG Retrieval Augmented Generation for LLMs

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Prompt Engineering Guide
Prompt engineering is a relatively new discipline for developing and optimizing prompts to efficiently use language models (LMs) for a wide variety of applications and research topics. Prompt engineering skills help to better understand the capabilities and limitations of large language models (LLMs).
Researchers use prompt engineering to improve the capacity of LLMs on a wide range of common and complex tasks such as question answering and arithmetic reasoning. Developers use prompt engineering to design robust and effective prompting techniques that interface with LLMs and other tools.
Prompt engineering is not just about designing and developing prompts. It encompasses a wide range of skills and techniques that are useful for interacting and developing with LLMs. It's an important skill to interface, build with, and understand capabilities of LLMs. You can use prompt engineering to improve safety of LLMs and build new capabilities like augmenting LLMs with domain knowledge and external tools.
Motivated by the high interest in developing with LLMs, we have created this new prompt engineering guide that contains all the latest papers, advanced prompting techniques, learning guides, model-specific prompting guides, lectures, references, new LLM capabilities, and tools related to prompt engineering.

@irthomasthomas irthomasthomas added embeddings vector embeddings and related tools llm Large Language Models finetuning Tools for finetuning of LLMs e.g. SFT or RLHF llm-experiments experiments with large language models prompt-tuning AI-Agents Autonomous AI agents using LLMs Models LLM and ML model repos and links llm-inference-engines Software to run inference on large language models RAG Retrieval Augmented Generation for LLMs base-model llm base models not finetuned for chat llm-evaluation Evaluating Large Language Models performance and behavior through human-written evaluation sets prompt-engineering Developing and optimizing prompts to efficiently use language models for various applications and re and removed base-model llm base models not finetuned for chat labels Jan 8, 2024
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Labels
AI-Agents Autonomous AI agents using LLMs embeddings vector embeddings and related tools finetuning Tools for finetuning of LLMs e.g. SFT or RLHF llm Large Language Models llm-evaluation Evaluating Large Language Models performance and behavior through human-written evaluation sets llm-experiments experiments with large language models llm-inference-engines Software to run inference on large language models Models LLM and ML model repos and links prompt-engineering Developing and optimizing prompts to efficiently use language models for various applications and re RAG Retrieval Augmented Generation for LLMs
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