Best AI tools for< Improve Language Models >

Langtrace AI is an open-source observability tool powered by Scale3 Labs that helps monitor, evaluate, and improve LLM (Large Language Model) applications. It collects and analyzes traces and metrics to provide insights into the ML pipeline, ensuring security through SOC 2 Type II certification. Langtrace supports popular LLMs, frameworks, and vector databases, offering end-to-end observability and the ability to build and deploy AI applications with confidence.

ThirdAI is a production-ready AI platform designed for enterprise use, offering out-of-the-box solutions that work at scale and provide 10x better price performance. The platform features enterprise SSO, LLM guardrails, built-in models, a no-code interface, and implicit feedback & RLHF. It allows for turnkey deployment of complex AI ecosystems, enabling business leaders to solve critical needs quickly. With a focus on security, scalability, and performance, ThirdAI helps drive innovation and achieve business goals from day one.

GPTionary is an AI-powered thesaurus tool that allows users to search for words or phrases quickly by describing them. It leverages the power of AI, specifically ChatGPT, to provide accurate and efficient results. Users from over 100 countries have accessed GPTionary in just 10 days, highlighting its global reach and popularity. The tool is designed to assist community leaders, such as school teachers and officials, in accessing its features for educational purposes. GPTionary ensures data security and user verification to prevent misuse and maintain a trusted user community.

Upstage is an Artificial General Intelligence (AGI) application designed to enhance work productivity by automating simple tasks and providing decision support through generative Business Intelligence (BI) knowledge and numerical understanding. The application offers various features such as Document AI, Solar LLM, and Developers Demo Playground, enabling users to automate tasks, extract key information from documents, and create conversational agents. Upstage aims to streamline workflow automation and improve efficiency in various domains such as healthcare, finance, and law.

Gretel.ai is a synthetic data platform designed for Generative AI applications. It allows users to generate artificial datasets with the same characteristics as real data, enabling the improvement of AI models without compromising privacy. The platform offers various features such as building synthetic data pipelines, rule-based data transformation, measuring data quality, and customizing language models. Gretel.ai is suitable for industries like finance, healthcare, and the public sector, providing a secure and efficient solution for data generation and model enhancement.

Cakewalk AI is an AI-powered platform designed to enhance team productivity by leveraging the power of ChatGPT and automation tools. It offers features such as team workspaces, prompt libraries, automation with prebuilt templates, and the ability to combine documents, images, and URLs. Users can automate tasks like updating product roadmaps, creating user personas, evaluating resumes, and more. Cakewalk AI aims to empower teams across various departments like Product, HR, Marketing, and Legal to streamline their workflows and improve efficiency.

WikeAI is an all-in-one AI platform that provides access to top AI models such as GPT-4, Claude3, Mistral, and Llama2. It offers professional-level cross-model integration, allowing users to experience powerful language understanding, speech synthesis, and visual generation technology without switching between multiple systems. WikeAI simplifies the process of using AI for content writing by generating blog articles, product descriptions, social media ads, and more in seconds. The platform offers different pricing plans tailored to various user needs, from casual users to language creators.

Trieve is an AI-first infrastructure API that offers a modern solution for search, recommendations, and RAG (Retrieve and Generate) tasks. It combines language models with tools for fine-tuning ranking and relevance, providing production-ready capabilities for building search, discovery, and RAG experiences. Trieve supports semantic vector search, full-text search using BM25 & SPLADE models, custom embedding models, hybrid search, and sub-sentence highlighting. With features like merchandising, relevance tuning, and self-hostable options, Trieve empowers companies to enhance their search capabilities and user experiences.

Super.AI provides Intelligent Document Processing (IDP) solutions powered by Large Language Models (LLMs) and human-in-the-loop (HITL) capabilities. It automates document processing tasks such as data extraction, classification, and redaction, enabling businesses to streamline their workflows and improve accuracy. Super.AI's platform leverages cutting-edge AI models from providers like Amazon, Google, and OpenAI to handle complex documents, ensuring high-quality outputs. With its focus on accuracy, flexibility, and scalability, Super.AI caters to various industries, including financial services, insurance, logistics, and healthcare.

Doclingo is an AI-powered document translation tool that supports translating documents in various formats such as PDF, Word, Excel, PowerPoint, SRT subtitles, ePub ebooks, AR&ZIP packages, and more. It utilizes large language models to provide accurate and professional translations, preserving the original layout of the documents. Users can enjoy a limited-time free trial upon registration, with the option to subscribe for more features. Doclingo aims to offer high-quality translation services through continuous algorithm improvements.

Ragobble is an audio to LLM data tool that allows you to easily convert audio files into text data that can be used to train large language models (LLMs). With Ragobble, you can quickly and easily create high-quality training data for your LLM projects.

Athina AI is a platform that provides research and guides for building safe and reliable AI products. It helps thousands of AI engineers in building safer products by offering tutorials, research papers, and evaluation techniques related to large language models. The platform focuses on safety, prompt engineering, hallucinations, and evaluation of AI models.

Metabob is an AI-powered code review tool that helps developers detect, explain, and fix coding problems. It utilizes proprietary graph neural networks to detect problems and LLMs to explain and resolve them, combining the best of both worlds. Metabob's AI is trained on millions of bug fixes performed by experienced developers, enabling it to detect complex problems that span across codebases and automatically generate fixes for them. It integrates with popular code hosting platforms such as GitHub, Bitbucket, Gitlab, and VS Code, and supports various programming languages including Python, Javascript, Typescript, Java, C++, and C.

Pongo is an AI-powered tool that helps reduce hallucinations in Large Language Models (LLMs) by up to 80%. It utilizes multiple state-of-the-art semantic similarity models and a proprietary ranking algorithm to ensure accurate and relevant search results. Pongo integrates seamlessly with existing pipelines, whether using a vector database or Elasticsearch, and processes top search results to deliver refined and reliable information. Its distributed architecture ensures consistent latency, handling a wide range of requests without compromising speed. Pongo prioritizes data security, operating at runtime with zero data retention and no data leaving its secure AWS VPC.

Prompt Engineering is a discipline focused on developing and optimizing prompts to efficiently utilize language models (LMs) for various applications and research topics. It involves skills to understand the capabilities and limitations of large language models, improving their performance on tasks like question answering and arithmetic reasoning. Prompt engineering is essential for designing robust prompting techniques that interact with LLMs and other tools, enhancing safety and building new capabilities by augmenting LLMs with domain knowledge and external tools.

MaestroQA is a comprehensive Call Center Quality Assurance Software that offers a range of products and features to enhance QA processes. It provides customizable report builders, scorecard builders, calibration workflows, coaching workflows, automated QA workflows, screen capture, accurate transcriptions, root cause analysis, performance dashboards, AI grading assist, analytics, and integrations with various platforms. The platform caters to industries like eCommerce, financial services, gambling, insurance, B2B software, social media, and media, offering solutions for QA managers, team leaders, and executives.

Kapa.ai is an AI documentation assistant that provides instant AI answers to technical questions. It turns knowledge bases into reliable AI assistants powered by large language models, helping organizations improve user experience by eliminating response waiting time and identifying documentation gaps. The platform offers off-the-shelf integrations, feedback loop for improved answers, and automatic updates to stay current with changes in documentation.

PygmalionAI is an open-source AI project focused on creating large language models for chat and role-play purposes. It offers a platform for users to engage in interactive conversations, storytelling, and adventure scenarios. The project aims to enhance user experiences by providing advanced AI capabilities for natural language processing and communication.

Omost is an AI-driven application that leverages Large Language Models (LLMs) to convert coding capabilities into image generation and composition. By utilizing pretrained LLM models, Omost enables users to create high-quality visual content from simple text prompts. The technology behind Omost revolutionizes image creation by integrating AI with LLMs, offering users a powerful tool for enhancing creativity and efficiency in various industries.

Infinipilot.AI is an AI co-pilot application designed for macOS users to enhance productivity and streamline various tasks. It offers features such as autocomplete, style and grammar fixes, translation, developer utilities, and AI-driven question answering. The application prioritizes privacy by using local language models and provides accessibility features like text-to-speech and speech-to-text functionalities. Infinipilot.AI integrates with various AI models like OpenAI and Claude, ensuring efficient performance and continuous updates. The application also offers discounts for students and non-profit organizations, along with a 14-day money-back guarantee.

RAG-FiT is a library designed to improve Language Models' ability to use external information by fine-tuning models on specially created RAG-augmented datasets. The library assists in creating training data, training models using parameter-efficient finetuning (PEFT), and evaluating performance using RAG-specific metrics. It is modular, customizable via configuration files, and facilitates fast prototyping and experimentation with various RAG settings and configurations.

Uncheatable Eval is a tool designed to assess the language modeling capabilities of LLMs on real-time, newly generated data from the internet. It aims to provide a reliable evaluation method that is immune to data leaks and cannot be gamed. The tool supports the evaluation of Hugging Face AutoModelForCausalLM models and RWKV models by calculating the sum of negative log probabilities on new texts from various sources such as recent papers on arXiv, new projects on GitHub, news articles, and more. Uncheatable Eval ensures that the evaluation data is not included in the training sets of publicly released models, thus offering a fair assessment of the models' performance.

RAGoon is a high-level library designed for batched embeddings generation, fast web-based RAG (Retrieval-Augmented Generation) processing, and quantized indexes processing. It provides NLP utilities for multi-model embedding production, high-dimensional vector visualization, and enhancing language model performance through search-based querying, web scraping, and data augmentation techniques.

This repository contains code for training reward models for Deep Reinforcement Learning-based Reward-modulated Hierarchical Fine-tuning (DRL-based RLHF), Iterative Selection Fine-tuning (Rejection sampling fine-tuning), and iterative Decision Policy Optimization (DPO). The reward models are trained using a Bradley-Terry model based on the Gemma and Mistral language models. The resulting reward models achieve state-of-the-art performance on the RewardBench leaderboard for reward models with base models of up to 13B parameters.

This leaderboard evaluates the hallucination rate of various Large Language Models (LLMs) when summarizing documents. It uses a model trained by Vectara to detect hallucinations in LLM outputs. The leaderboard includes models from OpenAI, Anthropic, Google, Microsoft, Amazon, and others. The evaluation is based on 831 documents that were summarized by all the models. The leaderboard shows the hallucination rate, factual consistency rate, answer rate, and average summary length for each model.

Awesome RAG is a curated list of retrieval-augmented generation (RAG) in large language models. It includes papers, surveys, general resources, lectures, talks, tutorials, workshops, tools, and other collections related to retrieval-augmented generation. The repository aims to provide a comprehensive overview of the latest advancements, techniques, and applications in the field of RAG.

This repository includes papers and blogs about Efficient Transformers, Length Extrapolation, Long Term Memory, Retrieval Augmented Generation(RAG), and Evaluation for Long Context Modeling.

This repository does not provide a tool, but rather a collection of resources and strategies for academics in the field of artificial intelligence who are feeling depressed or overwhelmed by the rapid advancements in the field. The resources include articles, blog posts, and other materials that offer advice on how to cope with the challenges of working in a fast-paced and competitive environment.

The repository 'Awesome-LLM-Preference-Learning' is the official repository of a survey paper titled 'Towards a Unified View of Preference Learning for Large Language Models: A Survey'. It contains a curated list of papers related to preference learning for Large Language Models (LLMs). The repository covers various aspects of preference learning, including on-policy and off-policy methods, feedback mechanisms, reward models, algorithms, evaluation techniques, and more. The papers included in the repository explore different approaches to aligning LLMs with human preferences, improving mathematical reasoning in LLMs, enhancing code generation, and optimizing language model performance.

This book aims to provide readers with a comprehensive understanding of large language model technology, including its basic principles, key technologies, and application prospects. Through in-depth research and practice, we can continuously explore and improve large language model technology, and contribute to the development of the field of artificial intelligence.

Awesome Generative AI & LLM APIs is a curated list of useful APIs that allow developers to integrate generative models into their applications without building the models from scratch. These APIs provide an interface for generating text, images, or other content, and include pre-trained language models for various tasks. The goal of this project is to create a hub for developers to create innovative applications, enhance user experiences, and drive progress in the AI field.

This repository is a collection of papers on leveraging Large Language Models (LLMs) in Graph Tasks. It provides a comprehensive overview of how LLMs can enhance graph-related tasks by combining them with traditional Graph Neural Networks (GNNs). The integration of LLMs with GNNs allows for capturing both structural and contextual aspects of nodes in graph data, leading to more powerful graph learning. The repository includes summaries of various models that leverage LLMs to assist in graph-related tasks, along with links to papers and code repositories for further exploration.

Awesome-Graph-LLM is a curated collection of research papers exploring the intersection of graph-based techniques with Large Language Models (LLMs). The repository aims to bridge the gap between LLMs and graph structures prevalent in real-world applications by providing a comprehensive list of papers covering various aspects of graph reasoning, node classification, graph classification/regression, knowledge graphs, multimodal models, applications, and tools. It serves as a valuable resource for researchers and practitioners interested in leveraging LLMs for graph-related tasks.

The Next-Generation LLM-based Recommender Systems Survey is a comprehensive overview of the latest advancements in recommender systems leveraging Large Language Models (LLMs). The survey covers various paradigms, approaches, and applications of LLMs in recommendation tasks, including generative and non-generative models, multimodal recommendations, personalized explanations, and industrial deployment. It discusses the comparison with existing surveys, different paradigms, and specific works in the field. The survey also addresses challenges and future directions in the domain of LLM-based recommender systems.

The collection is actively updated with the help of an internal literature search engine.

专门优化和翻译不同LLM的提示词的专家，基于用户选择和LLM特性。

Professionally finds top custom GPT models for specific topics

A GPT that helps you to find the best HuggingFace resources for your project

An assistant to help you understand transfer learning better

I assist with Langflow CustomComponents.

Assists with structuring knowledge files for GPTs

Fluency, one story at a time

AI Prompt Engineer for chat platforms

Expert in refining custom GPT model instructions.

I'm a ML engineer who formats code.

Helps improve language skills through interactive scenarios and feedback.

당신의 현재 스피킹 점수에 만족하시나요? 만약 '아니오'라면, 지금이 변화할 때입니다. 저희 연습모드와 프리토킹으로 이미 400명의 학생이 자신의 기록을 갈아치웠습니다. 다음은 당신 차례입니다. 더 이상 미루지 마세요!

A visual language learning aid exploring deep meanings and nuances.

A digital dictionary companion offering definitions, pronunciations, and language insights.

把任何語言翻譯成繁體中文Translate any language into Traditional Chinese.

Friendly Greek language tutor for travelers

A personalized translation assistant, adapting to user preferences and language proficiency.

论文润色降重助手，专注于提高语言流畅度和原创性

Помогает изучать казахский язык.

直接输入文本，将任意语言翻译成流畅日语