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A full-featured & carefully designed adaptive prompt for Bash & Zsh
Plug in and Play Implementation of Tree of Thoughts: Deliberate Problem Solving with Large Language Models that Elevates Model Reasoning by atleast 70%
Prompt Engineering, Generative AI, and LLM Guide by Learn Prompting | Join our discord for the largest Prompt Engineering learning community
This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc
一款提示词优化器，助力于编写高质量的提示词
Prompt Engineering | Prompt Versioning | Use GPT or other prompt based models to get structured output. Join our discord for Prompt-Engineering, LLMs and other latest research
Official repository of OFA (ICML 2022). Paper: OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework
A framework for prompt tuning using Intent-based Prompt Calibration
ClickPrompt - Streamline your prompt design, with ClickPrompt, you can easily view, share, and run these prompts with just one click. ClickPrompt 用于一键轻松查看、分享和执行您的 Prompt。
Your Automatic Prompt Engineering Assistant for GenAI Applications
An optimized deep prompt tuning strategy comparable to fine-tuning across scales and tasks
Generalist and Lightweight Model for Named Entity Recognition (Extract any entity types from texts) @ NAACL 2024
[ICLR 2024] Official implementation of " 🦙 Time-LLM: Time Series Forecasting by Reprogramming Large Language Models"
Awesome resources for in-context learning and prompt engineering: Mastery of the LLMs such as ChatGPT, GPT-3, and FlanT5, with up-to-date and cutting-edge updates.
A playground of highly experimental prompts, tools & scripts for machine intelligence models from DeepSeek, OpenAI, Anthropic, Meta, Mistral, Google, xAI & others.
Streamlines and simplifies prompt design for both developers and non-technical users with a low code approach.
A novel method to tune language models. Codes and datasets for paper ``GPT understands, too''.
Promptr is a CLI tool that applies plain language instructions to the filesystem. Instructions can utilize a liquidjs based templating system. Use cases include refactoring, code generation, and experimentation.
A curated list of prompt-based paper in computer vision and vision-language learning.