prompt-tuning

16 projetos partilham este topic do GitHub

Linhas conectam membros que estão mensuravelmente relacionados entre si. O tamanho do ponto reflete estrelas.

🧬 Membros

prompt-optimizer

An AI prompt optimizer for writing better prompts and getting better AI results.

★ 32.8k

Awesome-Prompt-Engineering

This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative…

★ 6.2k

Learn_Prompting

Prompt Engineering, Generative AI, and LLM Guide by Learn Prompting | Join our discord for the largest Prompt…

★ 4.7k

Promptify

Prompt Engineering | Prompt Versioning | Use GPT or other prompt based models to get structured output. Join…

★ 4.6k

tree-of-thoughts

Plug in and Play Implementation of Tree of Thoughts: Deliberate Problem Solving with Large Language Models…

★ 4.6k

GLiNER

Generalist and Lightweight Model for Named Entity Recognition (Extract any entity types from texts)

★ 3.5k

DecryptPrompt

总结Prompt&LLM论文，开源数据&模型，AIGC应用

★ 3.4k

Time-LLM

[ICLR 2024] Official implementation of " 🦙 Time-LLM: Time Series Forecasting by Reprogramming Large…

★ 2.7k

OFA

Official repository of OFA (ICML 2022). Paper: OFA: Unifying Architectures, Tasks, and Modalities Through a…

★ 2.6k

YiVal

Your Automatic Prompt Engineering Assistant for GenAI Applications

★ 2.1k

promptr

Promptr is a CLI tool that applies plain language instructions to the filesystem. Instructions can utilize a…

★ 950

KG_RAG

Empower Large Language Models (LLM) using Knowledge Graph based Retrieval-Augmented Generation (KG-RAG) for…

★ 941

Awesome-LLM4RS-Papers

Large Language Model-enhanced Recommender System Papers

★ 764

step_into_llm

MindSpore online courses: Step into LLM

★ 480

Awesome-LLM-Prompt-Optimization

Awesome-LLM-Prompt-Optimization: a curated list of advanced prompt optimization and tuning methods in Large…

★ 412

TapeAgents

TapeAgents is a framework that facilitates all stages of the LLM Agent development lifecycle

★ 317

Medido a partir dos tópicos do GitHub compartilhados por ambos os projetos, ponderado pela raridade de cada tópico.