Best AI tools for< Evaluate A Language Model >

LlamaIndex is a leading data framework designed for building LLM (Large Language Model) applications. It allows enterprises to turn their data into production-ready applications by providing functionalities such as loading data from various sources, indexing data, orchestrating workflows, and evaluating application performance. The platform offers extensive documentation, community-contributed resources, and integration options to support developers in creating innovative LLM applications.

Entry Point AI is a modern AI optimization platform for fine-tuning proprietary and open-source language models. It provides a user-friendly interface to manage prompts, fine-tunes, and evaluations in one place. The platform enables users to optimize models from leading providers, train across providers, work collaboratively, write templates, import/export data, share models, and avoid common pitfalls associated with fine-tuning. Entry Point AI simplifies the fine-tuning process, making it accessible to users without the need for extensive data, infrastructure, or insider knowledge.

Flow AI is an advanced AI tool designed for evaluating and improving Large Language Model (LLM) applications. It offers a unique system for creating custom evaluators, deploying them with an API, and developing specialized LMs tailored to specific use cases. The tool aims to revolutionize AI evaluation and model development by providing transparent, cost-effective, and controllable solutions for AI teams across various domains.

Edelman is an AI tool that focuses on enterprise marketing communications. It offers generative AI solutions to help marcom teams enhance decision-making, boost insights, and drive results. The tool provides key strategy elements for successful change management, evaluates analytics and social listening tools, and explores large language models for marketing and communications teams.

Ottic is an AI tool designed to empower both technical and non-technical teams to test Language Model (LLM) applications efficiently and accelerate the development cycle. It offers features such as a 360º view of the QA process, end-to-end test management, comprehensive LLM evaluation, and real-time monitoring of user behavior. Ottic aims to bridge the gap between technical and non-technical team members, ensuring seamless collaboration and reliable product delivery.

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.

Athina AI Hub is an ultimate resource for AI development teams, offering a wide range of AI development blogs, research papers, and original content. It provides valuable insights into cutting-edge technologies such as Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI agents. Athina AI Hub aims to empower AI engineers, researchers, data scientists, and product developers by offering comprehensive resources and fostering innovation in the field of Artificial Intelligence.

Athina AI is a comprehensive platform designed to monitor, debug, analyze, and improve the performance of Large Language Models (LLMs) in production environments. It provides a suite of tools and features that enable users to detect and fix hallucinations, evaluate output quality, analyze usage patterns, and optimize prompt management. Athina AI supports integration with various LLMs and offers a range of evaluation metrics, including context relevancy, harmfulness, summarization accuracy, and custom evaluations. It also provides a self-hosted solution for complete privacy and control, a GraphQL API for programmatic access to logs and evaluations, and support for multiple users and teams. Athina AI's mission is to empower organizations to harness the full potential of LLMs by ensuring their reliability, accuracy, and alignment with business objectives.

LlamaIndex is a framework for building context-augmented Large Language Model (LLM) applications. It provides tools to ingest and process data, implement complex query workflows, and build applications like question-answering chatbots, document understanding systems, and autonomous agents. LlamaIndex enables context augmentation by combining LLMs with private or domain-specific data, offering tools for data connectors, data indexes, engines for natural language access, chat engines, agents, and observability/evaluation integrations. It caters to users of all levels, from beginners to advanced developers, and is available in Python and Typescript.

Confident AI is an open-source evaluation infrastructure for Large Language Models (LLMs). It provides a centralized platform to judge LLM applications, ensuring substantial benefits and addressing any weaknesses in LLM implementation. With Confident AI, companies can define ground truths to ensure their LLM is behaving as expected, evaluate performance against expected outputs to pinpoint areas for iterations, and utilize advanced diff tracking to guide towards the optimal LLM stack. The platform offers comprehensive analytics to identify areas of focus and features such as A/B testing, evaluation, output classification, reporting dashboard, dataset generation, and detailed monitoring to help productionize LLMs with confidence.

Datumbox is a machine learning platform that offers a powerful open-source Machine Learning Framework written in Java. It provides a large collection of algorithms, models, statistical tests, and tools to power up intelligent applications. The platform enables developers to build smart software and services quickly using its REST Machine Learning API. Datumbox API offers off-the-shelf Classifiers and Natural Language Processing services for applications like Sentiment Analysis, Topic Classification, Language Detection, and more. It simplifies the process of designing and training Machine Learning models, making it easy for developers to create innovative applications.

FinetuneDB is an AI fine-tuning platform that allows users to easily create and manage datasets to fine-tune LLMs, evaluate outputs, and iterate on production data. It integrates with open-source and proprietary foundation models, and provides a collaborative editor for building datasets. FinetuneDB also offers a variety of features for evaluating model performance, including human and AI feedback, automated evaluations, and model metrics tracking.

This is a unified DevOps platform to build AI applications. It provides a comprehensive set of tools and services to help developers build, deploy, and manage AI applications. The platform includes a variety of features such as a code editor, a debugger, a profiler, and a deployment manager. It also provides access to a variety of AI services, such as natural language processing, machine learning, and computer vision.

Stanford HAI is a research institute at Stanford University dedicated to advancing AI research, education, and policy to improve the human condition. The institute brings together researchers from a variety of disciplines to work on a wide range of AI-related projects, including developing new AI algorithms, studying the ethical and societal implications of AI, and creating educational programs to train the next generation of AI leaders. Stanford HAI is committed to developing human-centered AI technologies and applications that benefit all of humanity.

Easy Save AI is a comprehensive directory of Digital Marketing AI tools available online and curated by a digital marketing expert, Muritala Yusuf. Easy Save AI's primary objective is to ensure that AI is accessible to everyone. You can conveniently utilize our website to discover new AI tools and services or locate specific ones based on your requirements by Using our easy-to-use filter on the home page. AI technology is constantly progressing, and experts are continuously developing sophisticated models for various applications. Our directory includes an array of AI tools such as AI copywriters, text and image generators, AI transcription, SEO automation tools, and more. There is something suitable for every individual! Our website is committed to offering user-friendly AI tools and resources that can contribute to the success of you and your business in the digital era. We meticulously evaluate and curate each tool to ensure they possess valuable features and are accessible to both novices and experts. With the Easy Save AI platform, you can locate the AI tools you require and save valuable time and money. We sometimes have discounts on AI Tools and we always specify on the product page for you to use.

edu720 is a science-backed learning platform that uses AI and nanolearning to redefine how workforces learn and achieve their goals. It provides pre-built learning modules on various topics, including cybersecurity, privacy, and AI ethics. edu720's 360-degree approach ensures that all employees, regardless of their status or location, fully understand and absorb the knowledge conveyed.

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.

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.

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.

Weavel is an AI tool designed to revolutionize prompt engineering for large language models (LLMs). It offers features such as tracing, dataset curation, batch testing, and evaluations to enhance the performance of LLM applications. Weavel enables users to continuously optimize prompts using real-world data, prevent performance regression with CI/CD integration, and engage in human-in-the-loop interactions for scoring and feedback. Ape, the AI prompt engineer, outperforms competitors on benchmark tests and ensures seamless integration and continuous improvement specific to each user's use case. With Weavel, users can effortlessly evaluate LLM applications without the need for pre-existing datasets, streamlining the assessment process and enhancing overall performance.

The LLM course is divided into three parts: 1. 🧩 **LLM Fundamentals** covers essential knowledge about mathematics, Python, and neural networks. 2. 🧑‍🔬 **The LLM Scientist** focuses on building the best possible LLMs using the latest techniques. 3. 👷 **The LLM Engineer** focuses on creating LLM-based applications and deploying them. For an interactive version of this course, I created two **LLM assistants** that will answer questions and test your knowledge in a personalized way: * 🤗 **HuggingChat Assistant**: Free version using Mixtral-8x7B. * 🤖 **ChatGPT Assistant**: Requires a premium account. ## 📝 Notebooks A list of notebooks and articles related to large language models. ### Tools | Notebook | Description | Notebook | |----------|-------------|----------| | 🧐 LLM AutoEval | Automatically evaluate your LLMs using RunPod |  | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. |  | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. |  | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. |  | | 🌳 Model Family Tree | Visualize the family tree of merged models. |  | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. |  |

Yet Another Applied LLM Benchmark is a collection of diverse tests designed to evaluate the capabilities of language models in performing real-world tasks. The benchmark includes tests such as converting code, decompiling bytecode, explaining minified JavaScript, identifying encoding formats, writing parsers, and generating SQL queries. It features a dataflow domain-specific language for easily adding new tests and has nearly 100 tests based on actual scenarios encountered when working with language models. The benchmark aims to assess whether models can effectively handle tasks that users genuinely care about.

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.

A curated list of Generative AI projects, tools, artworks, and models

Advanced RAG Techniques is a comprehensive collection of cutting-edge Retrieval-Augmented Generation (RAG) tutorials aimed at enhancing the accuracy, efficiency, and contextual richness of RAG systems. The repository serves as a hub for state-of-the-art RAG enhancements, comprehensive documentation, practical implementation guidelines, and regular updates with the latest advancements. It covers a wide range of techniques from foundational RAG methods to advanced retrieval methods, iterative and adaptive techniques, evaluation processes, explainability and transparency features, and advanced architectures integrating knowledge graphs and recursive processing.

PIXIU is a project designed to support the development, fine-tuning, and evaluation of Large Language Models (LLMs) in the financial domain. It includes components like FinBen, a Financial Language Understanding and Prediction Evaluation Benchmark, FIT, a Financial Instruction Dataset, and FinMA, a Financial Large Language Model. The project provides open resources, multi-task and multi-modal financial data, and diverse financial tasks for training and evaluation. It aims to encourage open research and transparency in the financial NLP field.

The 'judges' repository is a small library designed for using and creating LLM-as-a-Judge evaluators. It offers a curated set of LLM evaluators in a low-friction format for various use cases, backed by research. Users can use these evaluators off-the-shelf or as inspiration for building custom LLM evaluators. The library provides two types of judges: Classifiers that return boolean values and Graders that return scores on a numerical or Likert scale. Users can combine multiple judges using the 'Jury' object and evaluate input-output pairs with the '.judge()' method. Additionally, the repository includes detailed instructions on picking a model, sending data to an LLM, using classifiers, combining judges, and creating custom LLM judges with 'AutoJudge'.

MultiPL-E is a system for translating unit test-driven neural code generation benchmarks to new languages. It is part of the BigCode Code Generation LM Harness and allows for evaluating Code LLMs using various benchmarks. The tool supports multiple versions with improvements and new language additions, providing a scalable and polyglot approach to benchmarking neural code generation. Users can access a tutorial for direct usage and explore the dataset of translated prompts on the Hugging Face Hub.

TrustLLM is a comprehensive study of trustworthiness in LLMs, including principles for different dimensions of trustworthiness, established benchmark, evaluation, and analysis of trustworthiness for mainstream LLMs, and discussion of open challenges and future directions. Specifically, we first propose a set of principles for trustworthy LLMs that span eight different dimensions. Based on these principles, we further establish a benchmark across six dimensions including truthfulness, safety, fairness, robustness, privacy, and machine ethics. We then present a study evaluating 16 mainstream LLMs in TrustLLM, consisting of over 30 datasets. The document explains how to use the trustllm python package to help you assess the performance of your LLM in trustworthiness more quickly. For more details about TrustLLM, please refer to project website.

Simple Transformers is a library based on the Transformers library by HuggingFace, allowing users to quickly train and evaluate Transformer models with only 3 lines of code. It supports various tasks such as Information Retrieval, Language Models, Encoder Model Training, Sequence Classification, Token Classification, Question Answering, Language Generation, T5 Model, Seq2Seq Tasks, Multi-Modal Classification, and Conversational AI.

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.

Garak is a free tool that checks if a Large Language Model (LLM) can be made to fail in a way that is undesirable. It probes for hallucination, data leakage, prompt injection, misinformation, toxicity generation, jailbreaks, and many other weaknesses. Garak's a free tool. We love developing it and are always interested in adding functionality to support applications.

Noema is a framework that enables developers to control a language model and choose the path it will follow. It integrates Python with llm's generations, allowing users to use LLM as a thought interpreter rather than a source of truth. Noema is built on llama.cpp and guidance's shoulders. It applies the declarative programming paradigm to a language model, providing a way to represent functions, descriptions, and transformations. Users can create subjects, think about tasks, and generate content through generators, selectors, and code generators. Noema supports ReAct prompting, visualization, and semantic Python functionalities, offering a versatile tool for automating tasks and guiding language models.

PocketGroq is a tool that provides advanced functionalities for text generation, web scraping, web search, and AI response evaluation. It includes features like an Autonomous Agent for answering questions, web crawling and scraping capabilities, enhanced web search functionality, and flexible integration with Ollama server. Users can customize the agent's behavior, evaluate responses using AI, and utilize various methods for text generation, conversation management, and Chain of Thought reasoning. The tool offers comprehensive methods for different tasks, such as initializing RAG, error handling, and tool management. PocketGroq is designed to enhance development processes and enable the creation of AI-powered applications with ease.

This practical free hands-on course focuses on Large Language models and their applications, providing a hands-on experience using models from OpenAI and the Hugging Face library. The course is divided into three major sections: Techniques and Libraries, Projects, and Enterprise Solutions. It covers topics such as Chatbots, Code Generation, Vector databases, LangChain, Fine Tuning, PEFT Fine Tuning, Soft Prompt tuning, LoRA, QLoRA, Evaluate Models, Knowledge Distillation, and more. Each section contains chapters with lessons supported by notebooks and articles. The course aims to help users build projects and explore enterprise solutions using Large Language Models.

PingPong is a benchmark designed for role-playing language models, focusing on evaluating conversational abilities through interactions with characters and test situations. The benchmark uses LLMs to emulate users in role-playing conversations, assessing criteria such as character portrayal, entertainment value, and fluency. Users can engage in dialogues with specific characters, like Kurisu, and evaluate the bot's responses based on predefined criteria. PingPong aims to provide a comprehensive evaluation method for language models, moving beyond single-turn interactions to more complex conversational scenarios.

A creative aide for designing new GPT models, skilled in ideation and prompting.

A witty yet succinct guide for HuggingFace, offering technical assistance on using the platform - based on their Learning Hub

Your purpose is to create the pytorch code to train language models using pytorch

大型语言模型的学习和训练指导专家

Expert in designing GPT models and translating user needs into technical specs.

Formador para la certificación de ML Engineer en GCP, con respuestas y explicaciones detalladas.

Your AI research aide for the latest in ML.

I automatically create and evaluate phone scripts, presenting a final draft.

A professional assistant for technical item evaluations in banking

A discerning VC evaluating web3 pitches

A VC advisor channeling A16z wisdom.

A gpt assistant that helps with analyzing a startup/market. The answers you get back is already structured to give you the core elements you would want to see in an investment memo/ market analysis

A critical thinker for analyzing questions and improving answers

Your personal A.I. learning hero when creating interactive e-learning content

A decisive entity that makes choices and explains reasoning.

Expert Speech-Language Pathologist offering tailored medical consultations.

Assess the level of English

Simulates the IELTS Writing Test, evaluates responses, and estimates band scores.

Evaluates and translates Instagram posts.

Decisive IELTS Task 2 Assessor