Best AI tools for< Perform Language Modeling >

NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and high-level mathematical functions to perform operations on these arrays. It is the fundamental package for scientific computing with Python and is used in a wide range of applications, including data science, machine learning, and image processing. NumPy is open source and distributed under a liberal BSD license, and is developed and maintained publicly on GitHub by a vibrant, responsive, and diverse community.

Julius is an AI-powered tool that helps users analyze data and files. It can perform various tasks such as generating visualizations, answering data questions, and performing statistical modeling. Julius is designed to save users time and effort by automating complex data analysis tasks.

Kolank is an AI tool that offers a unified API for various AI models, including Generative AI. It provides features such as load balancing, fallbacks, cost and performance metrics. Users can easily access and utilize AI models for tasks like text generation, image analysis, and video processing. Kolank simplifies the integration of AI capabilities into applications, making it a valuable resource for developers and businesses seeking to leverage AI technology.

heyCLI is a command-line interface (CLI) tool that allows users to interact with their Linux systems using natural language. It is designed to make it easier for users to perform common tasks without having to memorize complex commands. heyCLI is still in its early stages of development, but it has the potential to be a valuable tool for both new and experienced Linux users.

Sapling is a language model copilot and API for businesses. It provides real-time suggestions to help sales, support, and success teams more efficiently compose personalized responses. Sapling also offers a variety of features to help businesses improve their customer service, including: * Autocomplete Everywhere: Provides deep learning-powered autocomplete suggestions across all messaging platforms, allowing agents to compose replies more quickly. * Sapling Suggest: Retrieves relevant responses from a team response bank and allows agents to respond more quickly to customer inquiries by simply clicking on suggested responses in real time. * Snippet macros: Allow for quick insertion of common responses. * Grammar and language quality improvements: Sapling catches 60% more language quality issues than other spelling and grammar checkers using a machine learning system trained on millions of English sentences. * Enterprise teams can define custom settings for compliance and content governance. * Distribute knowledge: Ensure team knowledge is shared in a snippet library accessible on all your web applications. * Perform blazing fast search on your knowledge library for compliance, upselling, training, and onboarding.

ChatWithCloud is a command-line interface (CLI) tool that enables users to interact with AWS Cloud using natural language within the Terminal, powered by generative AI. It allows users to perform various tasks such as cost analysis, security analysis, troubleshooting, and fixing infrastructure issues without the need for an OpenAI API Key. The tool offers both a lifetime license option and a managed subscription model for users' convenience.

Avanzai is a workflow automation tool designed for financial services. It utilizes AI agents to transform financial datasets into actionable insights, simplifying financial data analysis. Users can build charts with public data, connect their own data pipelines, and leverage the platform to perform tasks such as macro analysis, instrument screening, and risk analytics. Avanzai offers a comprehensive suite of tools for financial institutions to optimize their portfolios, screen assets, and analyze risks efficiently.

GPT CLI is an all-in-one AI tool that allows users to build their own AI command-line interface tools using ChatGPT. It provides various plugins such as AI Commit, AI Command, AI Translate, and more, enabling users to streamline their workflow and automate tasks through natural language commands. With GPT CLI, users can easily generate Git commit messages, execute commands, translate text, and perform various other AI-powered tasks directly from the command line.

Anthropic is a research and deployment company founded in 2021 by former OpenAI researchers Dario Amodei, Daniela Amodei, and Geoffrey Irving. The company is developing large language models, including Claude, a multimodal AI model that can perform a variety of language-related tasks, such as answering questions, generating text, and translating languages.

Noometic AI is an AI tool that helps users discover creators using natural language processing. It goes beyond traditional keyword searches by analyzing text, images, and videos with its proprietary RAG system. The tool aims to provide a scalable solution similar to what talent agents do intuitively, enabling users to perform creator search, content analysis, and brand safety research.

ChatBotKit is a platform that helps you create and interact with chatbots, access a variety of tools and services, and also gives you access to pre-built apps that you can use to perform a wide range of tasks. With ChatBotKit, you can build custom GPT for your website, create AI widgets, explore AI solutions, create immersive and interactive AI experiences, craft compelling AI personas, enhance the learning experience with AI-powered educational tools, automate repetitive tasks and streamline your workflows with AI-powered automation tools, leverage the power of conversational AI to drive more sales and conversions, and enhance your customer support experience with intelligent chatbots.

pdfAssistant is a powerful AI chatbot designed to assist users with various PDF processing tasks. It offers a user-friendly chat-based interface that allows users to convert, watermark, merge, split, and perform other PDF-related operations using natural language commands. The application is powered by industry-leading PDF and AI technology, providing fast and accurate results. With pdfAssistant, users can work smarter and more efficiently by simplifying complex PDF software processes.

ChatGPT Deutsch is an intelligent chatbot tool developed by OpenAI that allows users to interact online with the large GPT language model through the OpenAI API function, enabling them to create text in AI language. The tool is equipped with many features to perform various tasks such as language translation, content creation, and programming support in just a few seconds. ChatGPT Deutsch offers unlimited conversation possibilities based on vast and reliable data sources from various information channels. Users of GPT Deutsch can start asking questions immediately without incurring any fees or complicated account registration.

GPTConsole is an AI-powered platform that helps developers build production-ready applications faster and more efficiently. Its AI agents can generate code for a variety of applications, including web applications, AI applications, and landing pages. GPTConsole also offers a range of features to help developers build and maintain their applications, including an AI agent that can learn your entire codebase and answer your questions, and a CLI tool for accessing agents directly from the command line.

Parity is a personal scheduling assistant that helps you save time by automating the process of scheduling meetings. It works with your favorite tools, including Zoom, Google Meet, and Microsoft Teams, and can coordinate with everyone else on the thread to find a time that works for everyone. You can also get a briefing of all your calendar events just by asking, and forward emails about events to Parity to add them to your calendar automatically. Parity is compatible with your Google and Outlook calendars, and is free to use.

Cuely is an AI-powered tool that helps users perform various tasks and improve their productivity within Slack. It offers a range of features, including drafting replies, checking grammar and spelling, summarizing text, translating languages, and providing advice on problems. Cuely is designed to be easy to use, with three ways to access its AI capabilities within Slack: using the /cue prompt command, mentioning @cuely in group chats, or messaging Cuely directly.

SearchGPTool is a free AI-powered search tool that offers advanced features for users to enhance their search experience. The tool utilizes artificial intelligence algorithms to provide accurate and relevant search results. Users can benefit from features such as natural language processing, image recognition, personalized recommendations, voice search, and real-time updates. SearchGPTool aims to revolutionize the way users search for information online by leveraging AI technology to deliver efficient and tailored search results.

Stack Spaces is an intelligent all-in-one workspace designed to elevate productivity by providing a central workspace and dashboard for product development. It offers a platform to manage knowledge, tasks, documents, and schedule in an organized, centralized, and simplified manner. The application integrates GPT-4 technology to tailor the workspace for users, allowing them to leverage large language models and customizable widgets. Users can centralize all apps and tools, ask questions, and perform intelligent searches to access relevant answers and insights. Stack Spaces aims to streamline workflows, eliminate context-switching, and optimize efficiency for users.

Bizway is a solo business planning software that uses AI to help businesses automate tasks, create plans, and make decisions. With Bizway, businesses can create AI assistants that can help with a variety of tasks, such as writing marketing content, performing market research, and providing customer support. Bizway also offers a library of pre-built AI assistants that can help businesses get started with using AI. Bizway is designed to be easy to use, with no coding required. It is also affordable, with plans starting at just $10 per month.

Cohere is a customer support platform that uses AI to help businesses resolve tickets faster and reduce costs. It offers a range of features, including automated ticket resolution, personalized answers, step-by-step guidance, and advanced analytics. Cohere integrates with existing support resources and can be implemented quickly and easily. It has been used by leading companies to achieve industry-leading outcomes, including Ramp, Loom, Rippling, OpenPhone, Flock Safety, and Podium.

This repository contains a comprehensive collection of 63 must-know Large Language Models (LLMs) interview questions. It covers topics such as the architecture of LLMs, transformer models, attention mechanisms, training processes, encoder-decoder frameworks, differences between LLMs and traditional statistical language models, handling context and long-term dependencies, transformers for parallelization, applications of LLMs, sentiment analysis, language translation, conversation AI, chatbots, and more. The readme provides detailed explanations, code examples, and insights into utilizing LLMs for various tasks.

xLSTM is a new Recurrent Neural Network architecture based on ideas of the original LSTM. Through Exponential Gating with appropriate normalization and stabilization techniques and a new Matrix Memory it overcomes the limitations of the original LSTM and shows promising performance on Language Modeling when compared to Transformers or State Space Models. The package is based on PyTorch and was tested for versions >=1.8. For the CUDA version of xLSTM, you need Compute Capability >= 8.0. The xLSTM tool provides two main components: xLSTMBlockStack for non-language applications or integrating in other architectures, and xLSTMLMModel for language modeling or other token-based applications.

TokenFormer is a fully attention-based neural network architecture that leverages tokenized model parameters to enhance architectural flexibility. It aims to maximize the flexibility of neural networks by unifying token-token and token-parameter interactions through the attention mechanism. The architecture allows for incremental model scaling and has shown promising results in language modeling and visual modeling tasks. The codebase is clean, concise, easily readable, state-of-the-art, and relies on minimal dependencies.

This repository contains a collection of papers and resources related to Large Language Models (LLMs), including their applications in various domains such as text generation, translation, question answering, and dialogue systems. The repository also includes discussions on the ethical and societal implications of LLMs. **Description** This repository is a collection of papers and resources related to Large Language Models (LLMs). LLMs are a type of artificial intelligence (AI) that can understand and generate human-like text. They have a wide range of applications, including text generation, translation, question answering, and dialogue systems. **For Jobs** - **Content Writer** - **Copywriter** - **Editor** - **Journalist** - **Marketer** **AI Keywords** - **Large Language Models** - **Natural Language Processing** - **Machine Learning** - **Artificial Intelligence** - **Deep Learning** **For Tasks** - **Generate text** - **Translate text** - **Answer questions** - **Engage in dialogue** - **Summarize text**

The LLMEvaluation repository is a comprehensive compendium of evaluation methods for Large Language Models (LLMs) and LLM-based systems. It aims to assist academics and industry professionals in creating effective evaluation suites tailored to their specific needs by reviewing industry practices for assessing LLMs and their applications. The repository covers a wide range of evaluation techniques, benchmarks, and studies related to LLMs, including areas such as embeddings, question answering, multi-turn dialogues, reasoning, multi-lingual tasks, ethical AI, biases, safe AI, code generation, summarization, software performance, agent LLM architectures, long text generation, graph understanding, and various unclassified tasks. It also includes evaluations for LLM systems in conversational systems, copilots, search and recommendation engines, task utility, and verticals like healthcare, law, science, financial, and others. The repository provides a wealth of resources for evaluating and understanding the capabilities of LLMs in different domains.

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.

Awesome LLM compression research papers and tools to accelerate LLM training and inference.

LOTUS (LLMs Over Tables of Unstructured and Structured Data) is a query engine that provides a declarative programming model and an optimized query engine for reasoning-based query pipelines over structured and unstructured data. It offers a simple and intuitive Pandas-like API with semantic operators for fast and easy LLM-powered data processing. The tool implements a semantic operator programming model, allowing users to write AI-based pipelines with high-level logic and leaving the rest of the work to the query engine. LOTUS supports various semantic operators like sem_map, sem_filter, sem_extract, sem_agg, sem_topk, sem_join, sem_sim_join, and sem_search, enabling users to perform tasks like mapping records, filtering data, aggregating records, and more. The tool also supports different model classes such as LM, RM, and Reranker for language modeling, retrieval, and reranking tasks respectively.

EOLE is an open language modeling toolkit based on PyTorch. It aims to provide a research-friendly approach with a comprehensive yet compact and modular codebase for experimenting with various types of language models. The toolkit includes features such as versatile training and inference, dynamic data transforms, comprehensive large language model support, advanced quantization, efficient finetuning, flexible inference, and tensor parallelism. EOLE is a work in progress with ongoing enhancements in configuration management, command line entry points, reproducible recipes, core API simplification, and plans for further simplification, refactoring, inference server development, additional recipes, documentation enhancement, test coverage improvement, logging enhancements, and broader model support.

The DALM (Domain Adapted Language Modeling) toolkit is designed to unify general LLMs with vector stores to ground AI systems in efficient, factual domains. It provides developers with tools to build on top of Arcee's open source Domain Pretrained LLMs, enabling organizations to deeply tailor AI according to their unique intellectual property and worldview. The toolkit contains code for fine-tuning a fully differential Retrieval Augmented Generation (RAG-end2end) architecture, incorporating in-batch negative concept alongside RAG's marginalization for efficiency. It includes training scripts for both retriever and generator models, evaluation scripts, data processing codes, and synthetic data generation code.

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

The 'llms' repository is a comprehensive guide on Large Language Models (LLMs), covering topics such as language modeling, applications of LLMs, statistical language modeling, neural language models, conditional language models, evaluation methods, transformer-based language models, practical LLMs like GPT and BERT, prompt engineering, fine-tuning LLMs, retrieval augmented generation, AI agents, and LLMs for computer vision. The repository provides detailed explanations, examples, and tools for working with LLMs.

This project explores the capability of Large Language Models (LLMs) to perform regression tasks using in-context examples. It compares the performance of LLMs like GPT-4 and Claude 3 Opus with traditional supervised methods such as Linear Regression and Gradient Boosting. The project provides preprints and results demonstrating the strong performance of LLMs in regression tasks. It includes datasets, models used, and experiments on adaptation and contamination. The code and data for the experiments are available for interaction and analysis.

Awesome-LLM-Large-Language-Models-Notes is a repository that provides a comprehensive collection of information on various Large Language Models (LLMs) classified by year, size, and name. It includes details on known LLM models, their papers, implementations, and specific characteristics. The repository also covers LLM models classified by architecture, must-read papers, blog articles, tutorials, and implementations from scratch. It serves as a valuable resource for individuals interested in understanding and working with LLMs in the field of Natural Language Processing (NLP).

LLM-PowerHouse is a comprehensive and curated guide designed to empower developers, researchers, and enthusiasts to harness the true capabilities of Large Language Models (LLMs) and build intelligent applications that push the boundaries of natural language understanding. This GitHub repository provides in-depth articles, codebase mastery, LLM PlayLab, and resources for cost analysis and network visualization. It covers various aspects of LLMs, including NLP, models, training, evaluation metrics, open LLMs, and more. The repository also includes a collection of code examples and tutorials to help users build and deploy LLM-based applications.

This repository focuses on test-time computing, exploring various strategies such as test-time adaptation, modifying the input, editing the representation, calibrating the output, test-time reasoning, and search strategies. It covers topics like self-supervised test-time training, in-context learning, activation steering, nearest neighbor models, reward modeling, and multimodal reasoning. The repository provides resources including papers and code for researchers and practitioners interested in enhancing the reasoning capabilities of large language models.

LLM-Synthetic-Data is a repository focused on real-time, fine-grained LLM-Synthetic-Data generation. It includes methods, surveys, and application areas related to synthetic data for language models. The repository covers topics like pre-training, instruction tuning, model collapse, LLM benchmarking, evaluation, and distillation. It also explores application areas such as mathematical reasoning, code generation, text-to-SQL, alignment, reward modeling, long context, weak-to-strong generalization, agent and tool use, vision and language, factuality, federated learning, generative design, and safety.

InstructGraph is a framework designed to enhance large language models (LLMs) for graph-centric tasks by utilizing graph instruction tuning and preference alignment. The tool collects and decomposes 29 standard graph datasets into four groups, enabling LLMs to better understand and generate graph data. It introduces a structured format verbalizer to transform graph data into a code-like format, facilitating code understanding and generation. Additionally, it addresses hallucination problems in graph reasoning and generation through direct preference optimization (DPO). The tool aims to bridge the gap between textual LLMs and graph data, offering a comprehensive solution for graph-related tasks.

This repository contains a hand-curated list of great machine (deep) learning resources for Natural Language Processing (NLP) with a focus on Generative Pre-trained Transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), attention mechanism, Transformer architectures/networks, Chatbot, and transfer learning in NLP.

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