AI tools for zj
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EasyInstruct
EasyInstruct is a Python package proposed as an easy-to-use instruction processing framework for Large Language Models (LLMs) like GPT-4, LLaMA, ChatGLM in your research experiments. EasyInstruct modularizes instruction generation, selection, and prompting, while also considering their combination and interaction.
EasyEdit
EasyEdit is a Python package for edit Large Language Models (LLM) like `GPT-J`, `Llama`, `GPT-NEO`, `GPT2`, `T5`(support models from **1B** to **65B**), the objective of which is to alter the behavior of LLMs efficiently within a specific domain without negatively impacting performance across other inputs. It is designed to be easy to use and easy to extend.
KG-LLM-Papers
KG-LLM-Papers is a repository that collects papers integrating knowledge graphs (KGs) and large language models (LLMs). It serves as a comprehensive resource for research on the role of KGs in the era of LLMs, covering surveys, methods, and resources related to this integration.
KnowAgent
KnowAgent is a tool designed for Knowledge-Augmented Planning for LLM-Based Agents. It involves creating an action knowledge base, converting action knowledge into text for model understanding, and a knowledgeable self-learning phase to continually improve the model's planning abilities. The tool aims to enhance agents' potential for application in complex situations by leveraging external reservoirs of information and iterative processes.
LLMAgentPapers
LLM Agents Papers is a repository containing must-read papers on Large Language Model Agents. It covers a wide range of topics related to language model agents, including interactive natural language processing, large language model-based autonomous agents, personality traits in large language models, memory enhancements, planning capabilities, tool use, multi-agent communication, and more. The repository also provides resources such as benchmarks, types of tools, and a tool list for building and evaluating language model agents. Contributors are encouraged to add important works to the repository.
Prompt4ReasoningPapers
Prompt4ReasoningPapers is a repository dedicated to reasoning with language model prompting. It provides a comprehensive survey of cutting-edge research on reasoning abilities with language models. The repository includes papers, methods, analysis, resources, and tools related to reasoning tasks. It aims to support various real-world applications such as medical diagnosis, negotiation, etc.
Odyssey
Odyssey is a framework designed to empower agents with open-world skills in Minecraft. It provides an interactive agent with a skill library, a fine-tuned LLaMA-3 model, and an open-world benchmark for evaluating agent capabilities. The framework enables agents to explore diverse gameplay opportunities in the vast Minecraft world by offering primitive and compositional skills, extensive training data, and various long-term planning tasks. Odyssey aims to advance research on autonomous agent solutions by providing datasets, model weights, and code for public use.
KuiperLLama
KuiperLLama is a custom large model inference framework that guides users in building a LLama-supported inference framework with Cuda acceleration from scratch. The framework includes modules for architecture design, LLama2 model support, model quantization, Cuda basics, operator implementation, and fun tasks like text generation and storytelling. It also covers learning other commercial inference frameworks for comprehensive understanding. The project provides detailed tutorials and resources for developing and optimizing large models for efficient inference.
Foundations-of-LLMs
Foundations-of-LLMs is a comprehensive book aimed at readers interested in large language models, providing systematic explanations of foundational knowledge and introducing cutting-edge technologies. The book covers traditional language models, evolution of large language model architectures, prompt engineering, parameter-efficient fine-tuning, model editing, and retrieval-enhanced generation. Each chapter uses an animal as a theme to explain specific technologies, enhancing readability. The content is based on the author team's exploration and understanding of the field, with continuous monthly updates planned. The book includes a 'Paper List' for each chapter to track the latest advancements in related technologies.
ArcadiaScriptPublic
ArcadiaScriptPublic is a repository containing various scripts for learning and practicing JavaScript, Python, and Shell scripting. It is intended for testing and educational purposes only, and not for commercial use. The repository does not guarantee the legality, accuracy, completeness, or effectiveness of the scripts, and users are advised to use them at their own discretion. No resources from the repository are allowed to be republished or redistributed by any public account or self-media. The repository owner disclaims any responsibility for script-related issues, including losses or damages resulting from script errors. Users indirectly utilizing the scripts, such as setting up VPS or engaging in activities that violate national/regional laws or regulations, are solely responsible for any privacy leaks or consequences. If any entity or individual believes that the scripts in the project may infringe upon their rights, they should promptly notify and provide proof of identity and ownership, upon which the relevant scripts will be removed after verification. Anyone viewing or using the scripts in this project should carefully read and accept the disclaimer provided by zjk2017/ArcadiaScriptPublic, as the repository reserves the right to change or supplement the disclaimer at any time. Users must completely delete the downloaded content from their computers or phones within 24 hours of downloading, and any form of profit chain generation is strictly prohibited.
Scientific-LLM-Survey
Scientific Large Language Models (Sci-LLMs) is a repository that collects papers on scientific large language models, focusing on biology and chemistry domains. It includes textual, molecular, protein, and genomic languages, as well as multimodal language. The repository covers various large language models for tasks such as molecule property prediction, interaction prediction, protein sequence representation, protein sequence generation/design, DNA-protein interaction prediction, and RNA prediction. It also provides datasets and benchmarks for evaluating these models. The repository aims to facilitate research and development in the field of scientific language modeling.
LLM-and-Law
This repository is dedicated to summarizing papers related to large language models with the field of law. It includes applications of large language models in legal tasks, legal agents, legal problems of large language models, data resources for large language models in law, law LLMs, and evaluation of large language models in the legal domain.
LLM-Agents-Papers
A repository that lists papers related to Large Language Model (LLM) based agents. The repository covers various topics including survey, planning, feedback & reflection, memory mechanism, role playing, game playing, tool usage & human-agent interaction, benchmark & evaluation, environment & platform, agent framework, multi-agent system, and agent fine-tuning. It provides a comprehensive collection of research papers on LLM-based agents, exploring different aspects of AI agent architectures and applications.
aitviewer
A set of tools to visualize and interact with sequences of 3D data with cross-platform support on Windows, Linux, and macOS. It provides a native Python interface for loading and displaying SMPL[-H/-X], MANO, FLAME, STAR, and SUPR sequences in an interactive viewer. Users can render 3D data on top of images, edit SMPL sequences and poses, export screenshots and videos, and utilize a high-performance ModernGL-based rendering pipeline. The tool is designed for easy use and hacking, with features like headless mode, remote mode, animatable camera paths, and a built-in extensible GUI.
Awesome-LLM-Reasoning
**Curated collection of papers and resources on how to unlock the reasoning ability of LLMs and MLLMs.** **Description in less than 400 words, no line breaks and quotation marks.** Large Language Models (LLMs) have revolutionized the NLP landscape, showing improved performance and sample efficiency over smaller models. However, increasing model size alone has not proved sufficient for high performance on challenging reasoning tasks, such as solving arithmetic or commonsense problems. This curated collection of papers and resources presents the latest advancements in unlocking the reasoning abilities of LLMs and Multimodal LLMs (MLLMs). It covers various techniques, benchmarks, and applications, providing a comprehensive overview of the field. **5 jobs suitable for this tool, in lowercase letters.** - content writer - researcher - data analyst - software engineer - product manager **Keywords of the tool, in lowercase letters.** - llm - reasoning - multimodal - chain-of-thought - prompt engineering **5 specific tasks user can use this tool to do, in less than 3 words, Verb + noun form, in daily spoken language.** - write a story - answer a question - translate a language - generate code - summarize a document
awesome-LLM-game-agent-papers
This repository provides a comprehensive survey of research papers on large language model (LLM)-based game agents. LLMs are powerful AI models that can understand and generate human language, and they have shown great promise for developing intelligent game agents. This survey covers a wide range of topics, including adventure games, crafting and exploration games, simulation games, competition games, cooperation games, communication games, and action games. For each topic, the survey provides an overview of the state-of-the-art research, as well as a discussion of the challenges and opportunities for future work.