Best AI tools for< Language Researcher >

Neoform AI is an innovative AI tool that focuses on developing AI models specifically for African dialects. The platform aims to bridge the gap in AI technology by providing solutions tailored to the linguistic diversity of Africa. With a commitment to inclusivity and cultural representation, Neoform AI is revolutionizing the field of artificial intelligence by addressing the unique challenges faced by African languages. Through cutting-edge research and development, Neoform AI is paving the way for greater accessibility and accuracy in AI applications across the continent.

Shooketh is an AI bot that is fine-tuned on Shakespeare's literary works. It is built with the Vercel AI SDK and utilizes OpenAI GPT-3.5-turbo. Users can learn how to build their own bot like Shooketh by reading the provided guide. The bot can engage in conversations and provide insights inspired by Shakespeare's writings.

ChatTTS is an open-source text-to-speech model designed for dialogue scenarios, supporting both English and Chinese speech generation. Trained on approximately 100,000 hours of Chinese and English data, it delivers speech quality comparable to human dialogue. The tool is particularly suitable for tasks involving large language model assistants and creating dialogue-based audio and video introductions. It provides developers with a powerful and easy-to-use tool based on open-source natural language processing and speech synthesis technologies.

Storia AI is an AI tool designed to assist software engineering teams in understanding and generating code. It provides a Perplexity-like chat experience where users can interact with an AI expert that has access to the latest versions of open-source software. The tool aims to improve code understanding and generation by providing responses backed with links to implementations, API references, GitHub issues, and more. Storia AI is developed by a team of natural language processing researchers from Google and Amazon Alexa, with a mission to build the most reliable AI pair programmer for engineering teams.

LLM Clash is a web-based application that allows users to compare the outputs of different large language models (LLMs) on a given task. Users can input a prompt and select which LLMs they want to compare. The application will then display the outputs of the LLMs side-by-side, allowing users to compare their strengths and weaknesses.

Writefull is an AI-powered writing assistant that helps researchers and students write, paraphrase, copyedit, and more. It is designed to help non-native English speakers improve their writing and to make academic writing easier and faster. Writefull's AI is trained on millions of journal articles, so its edits are tailored to academic writing. It also offers a variety of AI widgets that can help you craft your sentences, such as the Academizer, Paraphraser, Title Generator, Abstract Generator, and GPT Detector.

Inspect is an open-source framework for large language model evaluations created by the UK AI Safety Institute. It provides built-in components for prompt engineering, tool usage, multi-turn dialog, and model graded evaluations. Users can explore various solvers, tools, scorers, datasets, and models to create advanced evaluations. Inspect supports extensions for new elicitation and scoring techniques through Python packages.

Locus is a free browser extension that uses natural language processing to help users quickly find information on any web page. It allows users to search for specific terms or concepts using natural language queries, and then instantly jumps to the relevant section of the page. Locus also integrates with AI-powered tools such as GPT-3.5 to provide additional functionality, such as summarizing text and generating code. With Locus, users can save time and improve their productivity when reading and researching online.

NepaliGPT is an AI-powered tool that provides language processing capabilities specifically tailored for the Nepali language. It offers users the ability to generate text, analyze content, and assist in research tasks. The tool is designed to help users with various language-related tasks, such as writing, proofreading, and information verification. With its advanced algorithms, NepaliGPT aims to enhance the user experience by providing accurate and efficient language processing solutions.

OdiaGenAI is a collaborative initiative focused on conducting research on Generative AI and Large Language Models (LLM) for the Odia Language. The project aims to leverage AI technology to develop Generative AI and LLM-based solutions for the overall development of Odisha and the Odia language through collaboration among Odia technologists. The initiative offers pre-trained models, codes, and datasets for non-commercial and research purposes, with a focus on building language models for Indic languages like Odia and Bengali.

Unsloth is an AI tool designed to make finetuning large language models like Llama-3, Mistral, Phi-3, and Gemma 2x faster, use 70% less memory, and with no degradation in accuracy. The tool provides documentation to help users navigate through training their custom models, covering essentials such as installing and updating Unsloth, creating datasets, running, and deploying models. Users can also integrate third-party tools and utilize platforms like Google Colab.

LangChain is a framework for developing applications powered by large language models (LLMs). It simplifies every stage of the LLM application lifecycle, including development, productionization, and deployment. LangChain consists of open-source libraries such as langchain-core, langchain-community, and partner packages. It also includes LangGraph for building stateful agents and LangSmith for debugging and monitoring LLM applications.

The website offers a brand new course titled 'Prompt Engineering for Everyone' to help users master the language of AI. With over 100 courses and 20+ learning paths, users can learn AI, Data Science, and other emerging technologies. The platform provides hands-on content designed by expert instructors, allowing users to gain practical, industry-relevant knowledge and skills. Users can earn certificates to showcase their expertise and build projects to demonstrate their skills. Trusted by 3 million learners globally, the platform offers a community of learners with a proven track record of success.

Ollama is an AI tool that allows users to access and utilize large language models such as Llama 3, Phi 3, Mistral, Gemma 2, and more. Users can customize and create their own models. The tool is available for macOS, Linux, and Windows platforms, offering a preview version for users to explore and utilize these models for various applications.

ReadWeb.ai is a free web-based tool that provides instant multi-language translation of web pages. It allows users to translate any webpage into up to 10 different languages with just one click. ReadWeb.ai also offers a unique bilingual reading experience, allowing users to view translations in an easy-to-understand, top-and-bottom format. This makes it an ideal tool for language learners, researchers, and anyone who needs to access information from websites in different languages.

MiniGPT-4 is a powerful AI tool that combines a vision encoder with a large language model (LLM) to enhance vision-language understanding. It can generate detailed image descriptions, create websites from handwritten drafts, write stories and poems inspired by images, provide solutions to problems shown in images, and teach users how to cook based on food photos. MiniGPT-4 is highly computationally efficient and easy to use, making it a valuable tool for a wide range of applications.

Floneum is a versatile AI-powered tool designed for language tasks. It offers a user-friendly interface to build workflows using large language models. With Floneum, users can securely extend functionality by writing plugins in various languages compiled to WebAssembly. The tool provides a sandboxed environment for plugins, ensuring limited resource access. With 41 built-in plugins, Floneum simplifies tasks such as text generation, search engine operations, file handling, Python execution, browser automation, and data manipulation.

Chat GPT is an AI-powered chatbot developed by OpenAI, a leading research company in the field of artificial intelligence. It is designed to understand and generate human-like text, making it a versatile tool for a wide range of applications. With its advanced language processing capabilities, Chat GPT can engage in natural conversations, answer questions, provide information, and even create creative content. It is accessible online and can be integrated into various platforms and applications to enhance their functionality.

The website offers an AI-powered tool for easy data visualization through natural language commands. Users can transform CSV data into various charts without the need for complex coding. The platform provides a wide range of chart types, smart AI support, and prioritizes data security and privacy. It simplifies data visualization tasks, making it intuitive and versatile for users to create visual insights effortlessly.

Iflow is an AI assistant application designed to help users efficiently acquire knowledge in various areas, whether it's for daily entertainment, general life knowledge, or professional academic research. It provides real-time answers to questions, summarizes lengthy articles, and assists in structuring documents to enhance creativity and productivity. With Iflow, users can easily enter a state of flow where knowledge flows effortlessly. The application covers a wide range of topics and is equipped with advanced natural language processing capabilities to cater to diverse user needs.

Awesome Khmer Language is a comprehensive collection of resources for the Khmer language, including tools, datasets, research papers, projects/models, blogs/slides, and miscellaneous items. It covers a wide range of topics related to Khmer language processing, such as character normalization, word segmentation, part-of-speech tagging, optical character recognition, text-to-speech, and more. The repository aims to support the development of natural language processing applications for the Khmer language by providing a diverse set of resources and tools for researchers and developers.

The Classical Language Toolkit (CLTK) is a Python library that provides natural language processing (NLP) capabilities for pre-modern languages. It offers a modular processing pipeline with pre-configured defaults and supports almost 20 languages. Users can install the latest version using pip and access detailed documentation on the official website. The toolkit is designed to meet the unique needs of researchers working with historical languages, filling a void in the NLP landscape that often neglects non-spoken languages and different research goals.

This repository contains language models for the Russian language, as well as their implementation and comparison. The models are trained on a dataset of ChatGPT-generated instructions and chats in Russian. They can be used for a variety of tasks, including question answering, text generation, and translation.

Verbiverse is a tool that uses a large language model to assist in reading PDFs and watching videos, aimed at improving language proficiency. It provides a more convenient and efficient way to use large models through predefined prompts, designed for those looking to enhance their language skills. The tool analyzes unfamiliar words and sentences in foreign language PDFs or video subtitles, providing better contextual understanding compared to traditional dictionary translations or ambiguous meanings. It offers features such as automatic loading of subtitles, word analysis by clicking or double-clicking, and a word database for collecting words. Users can run the tool on Windows x86_64 or ubuntu_22.04 x86_64 platforms by downloading the precompiled packages or by cloning the source code and setting up a virtual environment with Python. It is recommended to use a local model or smaller PDF files for testing due to potential token consumption issues with large files.

Sailor is a suite of open language models tailored for South-East Asia (SEA), focusing on languages such as Indonesian, Thai, Vietnamese, Malay, and Lao. Developed with careful data curation, Sailor models are designed to understand and generate text across diverse linguistic landscapes of the SEA region. Built from Qwen 1.5, Sailor encompasses models of varying sizes, spanning from 0.5B to 7B versions for different requirements. Benchmarking results demonstrate Sailor's proficiency in tasks such as question answering, commonsense reasoning, reading comprehension, and more in SEA languages.

LLPlayer is a specialized media player designed for language learning, offering unique features such as dual subtitles, AI-generated subtitles, real-time OCR, real-time translation, word lookup, and more. It supports multiple languages, online video playback, customizable settings, and integration with browser extensions. Written in C#/WPF, LLPlayer is free, open-source, and aims to enhance the language learning experience through innovative functionalities.

KanTV is an open-source project that focuses on studying and practicing state-of-the-art AI technology in real applications and scenarios, such as online TV playback, transcription, translation, and video/audio recording. It is derived from the original ijkplayer project and includes many enhancements and new features, including: * Watching online TV and local media using a customized FFmpeg 6.1. * Recording online TV to automatically generate videos. * Studying ASR (Automatic Speech Recognition) using whisper.cpp. * Studying LLM (Large Language Model) using llama.cpp. * Studying SD (Text to Image by Stable Diffusion) using stablediffusion.cpp. * Generating real-time English subtitles for English online TV using whisper.cpp. * Running/experiencing LLM on Xiaomi 14 using llama.cpp. * Setting up a customized playlist and using the software to watch the content for R&D activity. * Refactoring the UI to be closer to a real commercial Android application (currently only supports English). Some goals of this project are: * To provide a well-maintained "workbench" for ASR researchers interested in practicing state-of-the-art AI technology in real scenarios on mobile devices (currently focusing on Android). * To provide a well-maintained "workbench" for LLM researchers interested in practicing state-of-the-art AI technology in real scenarios on mobile devices (currently focusing on Android). * To create an Android "turn-key project" for AI experts/researchers (who may not be familiar with regular Android software development) to focus on device-side AI R&D activity, where part of the AI R&D activity (algorithm improvement, model training, model generation, algorithm validation, model validation, performance benchmark, etc.) can be done very easily using Android Studio IDE and a powerful Android phone.

DAMO-ConvAI is the official repository for Alibaba DAMO Conversational AI. It contains the codebase for various conversational AI models and tools developed by Alibaba Research. These models and tools cover a wide range of tasks, including natural language understanding, natural language generation, dialogue management, and knowledge graph construction. DAMO-ConvAI is released under the MIT license and is available for use by researchers and developers in the field of conversational AI.

This project aims to create a RESTful API server compatible with the OpenAI API using open-source backends like llama/llama2. With this project, various GPT tools/frameworks can be compatible with your own model. Key features include: - **Compatibility with OpenAI API**: The API server follows the OpenAI API structure, allowing seamless integration with existing tools and frameworks. - **Support for Multiple Backends**: The server supports both llama.cpp and pyllama backends, providing flexibility in model selection. - **Customization Options**: Users can configure model parameters such as temperature, top_p, and top_k to fine-tune the model's behavior. - **Batch Processing**: The API supports batch processing for embeddings, enabling efficient handling of multiple inputs. - **Token Authentication**: The server utilizes token authentication to secure access to the API. This tool is particularly useful for developers and researchers who want to integrate large language models into their applications or explore custom models without relying on proprietary APIs.

LLM-Blender is a framework for ensembling large language models (LLMs) to achieve superior performance. It consists of two modules: PairRanker and GenFuser. PairRanker uses pairwise comparisons to distinguish between candidate outputs, while GenFuser merges the top-ranked candidates to create an improved output. LLM-Blender has been shown to significantly surpass the best LLMs and baseline ensembling methods across various metrics on the MixInstruct benchmark dataset.

The Alignment Handbook provides robust training recipes for continuing pretraining and aligning language models with human and AI preferences. It includes techniques such as continued pretraining, supervised fine-tuning, reward modeling, rejection sampling, and direct preference optimization (DPO). The handbook aims to fill the gap in public resources on training these models, collecting data, and measuring metrics for optimal downstream performance.

This repository focuses on exploring tools that enhance the performance of language models for various tasks. It provides a structured list of literature relevant to tool-augmented language models, covering topics such as tool basics, tool use paradigm, scenarios, advanced methods, and evaluation. The repository includes papers, preprints, and books that discuss the use of tools in conjunction with language models for tasks like reasoning, question answering, mathematical calculations, accessing knowledge, interacting with the world, and handling non-textual modalities.

Evalchemy is a unified and easy-to-use toolkit for evaluating language models, focusing on post-trained models. It integrates multiple existing benchmarks such as RepoBench, AlpacaEval, and ZeroEval. Key features include unified installation, parallel evaluation, simplified usage, and results management. Users can run various benchmarks with a consistent command-line interface and track results locally or integrate with a database for systematic tracking and leaderboard submission.

This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.

MNN-LLM is a high-performance inference engine for large language models (LLMs) on mobile and embedded devices. It provides optimized implementations of popular LLM models, such as ChatGPT, BLOOM, and GPT-3, enabling developers to easily integrate these models into their applications. MNN-LLM is designed to be efficient and lightweight, making it suitable for resource-constrained devices. It supports various deployment options, including mobile apps, web applications, and embedded systems. With MNN-LLM, developers can leverage the power of LLMs to enhance their applications with natural language processing capabilities, such as text generation, question answering, and dialogue generation.

LLM.swift is a simple and readable library that allows you to interact with large language models locally with ease for macOS, iOS, watchOS, tvOS, and visionOS. It's a lightweight abstraction layer over `llama.cpp` package, so that it stays as performant as possible while is always up to date. Theoretically, any model that works on `llama.cpp` should work with this library as well. It's only a single file library, so you can copy, study and modify the code however you want.

LLM-jp-eval is a tool designed to automatically evaluate Japanese large language models across multiple datasets. It provides functionalities such as converting existing Japanese evaluation data to text generation task evaluation datasets, executing evaluations of large language models across multiple datasets, and generating instruction data (jaster) in the format of evaluation data prompts. Users can manage the evaluation settings through a config file and use Hydra to load them. The tool supports saving evaluation results and logs using wandb. Users can add new evaluation datasets by following specific steps and guidelines provided in the tool's documentation. It is important to note that using jaster for instruction tuning can lead to artificially high evaluation scores, so caution is advised when interpreting the results.

AlignBench is the first comprehensive evaluation benchmark for assessing the alignment level of Chinese large models across multiple dimensions. It includes introduction information, data, and code related to AlignBench. The benchmark aims to evaluate the alignment performance of Chinese large language models through a multi-dimensional and rule-calibrated evaluation method, enhancing reliability and interpretability.

CritiqueLLM is an official implementation of a model designed for generating informative critiques to evaluate large language model generation. It includes functionalities for data collection, referenced pointwise grading, referenced pairwise comparison, reference-free pairwise comparison, reference-free pointwise grading, inference for pointwise grading and pairwise comparison, and evaluation of the generated results. The model aims to provide a comprehensive framework for evaluating the performance of large language models based on human ratings and comparisons.

LangChain.dart is a Dart port of the popular LangChain Python framework created by Harrison Chase. LangChain provides a set of ready-to-use components for working with language models and a standard interface for chaining them together to formulate more advanced use cases (e.g. chatbots, Q&A with RAG, agents, summarization, extraction, etc.). The components can be grouped into a few core modules: * **Model I/O:** LangChain offers a unified API for interacting with various LLM providers (e.g. OpenAI, Google, Mistral, Ollama, etc.), allowing developers to switch between them with ease. Additionally, it provides tools for managing model inputs (prompt templates and example selectors) and parsing the resulting model outputs (output parsers). * **Retrieval:** assists in loading user data (via document loaders), transforming it (with text splitters), extracting its meaning (using embedding models), storing (in vector stores) and retrieving it (through retrievers) so that it can be used to ground the model's responses (i.e. Retrieval-Augmented Generation or RAG). * **Agents:** "bots" that leverage LLMs to make informed decisions about which available tools (such as web search, calculators, database lookup, etc.) to use to accomplish the designated task. The different components can be composed together using the LangChain Expression Language (LCEL).

A language self-assessment guide with mobile app voice interaction support.

Interactive language quiz

Master language complexities with tailored mind maps that enhance understanding and bolster memory. Explore linguistic patterns in a visually engaging way. 🧠🗺️

Advanced AI for immersive Yoruba language & cultural learning.

Your guide to Tamil language, culture, cuisine and history

Помогает изучать казахский язык.

💡 Inventor of languages

Schwäbisch alemannischer Chatbot - AlemannicGPT speaks and understands Svabian, Badenian and Swiss German dialects.

Comprehensive Norwegian course with interactive exercises and cultural insights.

Korean GPT

Ojekuaa ha ome’ẽ mba’éichapa oñepohano - Guarani ñe’ẽ

中文交流的韩语句子解析助手。

This GPT will help you learn Cajun French before it dies forever

A helpful guide for learning Kanji, using simple English and clear examples.

A French-speaking GPT for answering questions in French.

Kannada GPT

I'm a wizard who believes in magic.

Deep learning researcher explaining Google Gemini from PDFs.

Literal interpretation of the U.S. Constitution, emphasizing clear language.