prompt-learning

An Open-Source Framework for Prompt-Learning.

Must-read papers on prompt-based tuning for pre-trained language models.

Plug in and Play Implementation of Tree of Thoughts: Deliberate Problem Solving with Large Language Models that Elevates Model Reasoning by atleast 70%

This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc

A trend starts from "Chain of Thought Prompting Elicits Reasoning in Large Language Models".

Create. Use. Share. ChatGPT prompts

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.

《面向开发者的 ChatGPT 提示词工程》非官方版中英双语字幕 Unofficial subtitles of "ChatGPT Prompt Engineering for Developers"

A curated list of prompt-based paper in computer vision and vision-language learning.

Awesome papers on Language-Model-as-a-Service (LMaaS)

[EMNLP 2022] A Unified Framework and Analysis for Structured Knowledge Grounding with Text-to-Text Language Models

Reading list of Instruction-tuning. A trend starts from Natrural-Instruction (ACL 2022), FLAN (ICLR 2022) and T0 (ICLR 2022).

pCLUE: 1000000+多任务提示学习数据集

This repository contains a collection of papers and resources on Reasoning in Large Language Models.

Collection of papers and resources on Reasoning in Large Language Models (LLMs), including Chain-of-Thought (CoT), Instruction-Tuning, and others.

Collection of ChatGPT 3K+ Prompts from AIPRM, also provide i18n versions (Translate via ChatGPT 3.5). 包含 ChatGPT 3000 个以上的 Prompt 提示词 ，为所有开发者提供CSV和JSON数据格式

The code for our paper "NSP-BERT: A Prompt-based Zero-Shot Learner Through an Original Pre-training Task —— Next Sentence Prediction"

[ICLR 2023] Code for the paper "Binding Language Models in Symbolic Languages"

Code and datasets for the WWW2022 paper "KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation Extraction."

Align and Prompt: Video-and-Language Pre-training with Entity Prompts