Best AI tools for< Analyze Language Models >

AppTek is a global leader in artificial intelligence (AI) and machine learning (ML) technologies for automatic speech recognition (ASR), neural machine translation (NMT), natural language processing/understanding (NLP/U) and text-to-speech (TTS) technologies. The AppTek platform delivers industry-leading solutions for organizations across a breadth of global markets such as media and entertainment, call centers, government, enterprise business, and more. Built by scientists and research engineers who are recognized among the best in the world, AppTek’s solutions cover a wide array of languages/ dialects, channels, domains and demographics.

NinjaChat is an all-in-one AI platform that offers a suite of premium AI chatbots, an AI image generator, an AI music generator, and more—all seamlessly integrated into one powerful platform tailored to users' needs. It provides access to over 9 AI apps on one platform, featuring popular AI models like GPT-4, Claude 3, Mixtral, PDF analysis, image generation, and music composition. Users can chat with documents, generate images, and interact with multiple language models under one subscription.

NewsDigest.Ai is an AI-powered platform that provides 24/7 financial news updates. It utilizes advanced AI agents to gather news related to technology, economics, and geopolitics in multiple languages. Users can access real-time news content and stay informed about the latest developments in the financial world.

Dataku.ai is an advanced data extraction and analysis tool powered by AI technology. It offers seamless extraction of valuable insights from documents and texts, transforming unstructured data into structured, actionable information. The tool provides tailored data extraction solutions for various needs, such as resume extraction for streamlined recruitment processes, review insights for decoding customer sentiments, and leveraging customer data to personalize experiences. With features like market trend analysis and financial document analysis, Dataku.ai empowers users to make strategic decisions based on accurate data. The tool ensures precision, efficiency, and scalability in data processing, offering different pricing plans to cater to different user needs.

Promptech is an AI teamspace designed to streamline workflows and enhance productivity. It offers a range of features including AI assistants, a collaborative teamspace, and access to large language models (LLMs). Promptech is suitable for businesses of all sizes and can be used for a variety of tasks such as streamlining tasks, enhancing collaboration, and safeguarding IP. It is a valuable resource for technology leaders and provides a cost-effective AI solution for smaller teams and startups.

Stockpulse is an AI-powered platform that analyzes financial news and communities using Artificial Intelligence. It provides decision support for operations by collecting, filtering, and converting unstructured data into processable information. With extensive coverage of financial media sources globally, Stockpulse offers unique historical data, sentiment analysis, and AI-driven insights for various sectors in the financial markets.

Cohere is the leading AI platform for enterprise, offering products optimized for generative AI, search and discovery, and advanced retrieval. Their models are designed to enhance the global workforce, enabling businesses to thrive in the AI era. Cohere provides Command R+, Cohere Command, Cohere Embed, and Cohere Rerank for building efficient AI-powered applications. The platform also offers deployment options for enterprise-grade AI on any cloud or on-premises, along with developer resources like Playground, LLM University, and Developer Docs.

Thales Labs is a premier AI research lab and incubator empowering entrepreneurs and domain experts to revolutionize industries with large language models and web3. They focus on fostering innovation in sectors like Insurance, Finance, Healthcare, Pharma, Law, and Journalism. The user-friendly app allows experts to build AI applications using their natural language skills, with support from skilled engineers for complex challenges. Join Thales Labs to transform industries, unlock new opportunities, and create value with AI-driven innovation.

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.

aimlapi.com is an AI tool that offers 100+ AI models accessible via one API. It provides developers with a wide range of AI models for various tasks such as chat, language, image generation, and code processing. The platform is designed to be user-friendly, cost-efficient, and scalable, making it suitable for developers of all levels. With a focus on transparency, affordability, and compatibility with OpenAI, aimlapi.com aims to provide high-quality AI solutions to its users.

Denvr DataWorks AI Cloud is a cloud-based AI platform that provides end-to-end AI solutions for businesses. It offers a range of features including high-performance GPUs, scalable infrastructure, ultra-efficient workflows, and cost efficiency. Denvr DataWorks is an NVIDIA Elite Partner for Compute, and its platform is used by leading AI companies to develop and deploy innovative AI solutions.

Weam is an AI adoption platform designed for digital agencies to supercharge their operations with collaborative AI. It offers a comprehensive suite of tools for simplifying AI implementation, including project management, resource allocation, training modules, and ongoing support to ensure successful AI integration. Weam enables teams to interact and collaborate over their preferred LLMs, facilitating scalability, time-saving, and widespread AI adoption across the organization.

Allganize Inc. is a leading provider of enterprise AI solutions. Their platform enables businesses to build and deploy custom AI applications without the need for coding. Allganize's solutions are used by a variety of industries, including financial services, healthcare, and manufacturing.

AssemblyAI is an industry-leading Speech AI tool that offers powerful SpeechAI models for accurate transcription and understanding of speech. It provides breakthrough speech-to-text models, real-time captioning, and advanced speech understanding capabilities. AssemblyAI is designed to help developers build world-class products with unmatched accuracy and transformative audio intelligence.

DocsChat is an AI-powered document conversation tool that revolutionizes the way users interact with various types of documents. It leverages OCR-powered AI technology to streamline document interactions, making it easier to comprehend, exchange knowledge, troubleshoot, and navigate through different document types. With a focus on enhancing user experiences across reading, research, business, legal, and training domains, DocsChat offers a versatile platform for effortless and personalized document engagement.

Avanzai is an AI tool designed for financial services, providing intelligent automation to asset managers. It streamlines operations, enhances decision-making, and transforms data into actionable strategies. With AI-powered reports, automated portfolio management, data connectivity, and customizable agents, Avanzai empowers financial firms to optimize portfolios and make informed decisions.

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.

Qwen is an AI tool that focuses on developing and releasing various language models, including dense models, coding models, mathematical models, and vision language models. The Qwen family offers open-source models with different parameter ranges to cater to various user needs, such as production use, mobile applications, coding assistance, mathematical problem-solving, and visual understanding of images and videos. Qwen aims to enhance intelligence and provide smarter and more knowledgeable models for developers and users.

Text Generator is an AI-powered text generation tool that provides users with accurate, fast, and flexible text generation capabilities. With its advanced large neural networks, Text Generator offers a cost-effective solution for various text-related tasks. The tool's intuitive 'prompt engineering' feature allows users to guide text creation by providing keywords and natural questions, making it adaptable for tasks such as classification and sentiment analysis. Text Generator ensures industry-leading security by never storing personal information on its servers. The tool's continuous training ensures that its AI remains up-to-date with the latest events. Additionally, Text Generator offers a range of features including speech-to-text API, text-to-speech API, and code generation, supporting multiple spoken languages and programming languages. With its one-line migration from OpenAI's text generation hub and a shared embedding for multiple spoken languages, images, and code, Text Generator empowers users with powerful search, fingerprinting, tracking, and classification capabilities.

Salad is a distributed GPU cloud platform that offers fully managed and massively scalable services for AI applications. It provides the lowest priced AI transcription in the market, with features like image generation, voice AI, computer vision, data collection, and batch processing. Salad democratizes cloud computing by leveraging consumer GPUs to deliver cost-effective AI/ML inference at scale. The platform is trusted by hundreds of machine learning and data science teams for its affordability, scalability, and ease of deployment.

This repository is a collection of papers focused on understanding the internal mechanism of large language models (LLM). It includes research on topics such as how LLMs handle multilingualism, learn in-context, and handle factual associations. The repository aims to provide insights into the inner workings of transformer-based language models through a curated list of papers and surveys.

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.

Open LLMs is a repository containing various Large Language Models licensed for commercial use. It includes models like T5, GPT-NeoX, UL2, Bloom, Cerebras-GPT, Pythia, Dolly, and more. These models are designed for tasks such as transfer learning, language understanding, chatbot development, code generation, and more. The repository provides information on release dates, checkpoints, papers/blogs, parameters, context length, and licenses for each model. Contributions to the repository are welcome, and it serves as a resource for exploring the capabilities of different language models.

SakuraLLM is a project focused on building large language models for Japanese to Chinese translation in the light novel and galgame domain. The models are based on open-source large models and are pre-trained and fine-tuned on general Japanese corpora and specific domains. The project aims to provide high-performance language models for galgame/light novel translation that are comparable to GPT3.5 and can be used offline. It also offers an API backend for running the models, compatible with the OpenAI API format. The project is experimental, with version 0.9 showing improvements in style, fluency, and accuracy over GPT-3.5.

Nexa SDK is a comprehensive toolkit supporting ONNX and GGML models for text generation, image generation, vision-language models (VLM), and text-to-speech (TTS) capabilities. It offers an OpenAI-compatible API server with JSON schema mode and streaming support, along with a user-friendly Streamlit UI. Users can run Nexa SDK on any device with Python environment, with GPU acceleration supported. The toolkit provides model support, conversion engine, inference engine for various tasks, and differentiating features from other tools.

MisguidedAttention is a collection of prompts designed to challenge the reasoning abilities of large language models by presenting them with modified versions of well-known thought experiments, riddles, and paradoxes. The goal is to assess the logical deduction capabilities of these models and observe any shortcomings or fallacies in their responses. The repository includes a variety of prompts that test different aspects of reasoning, such as decision-making, probability assessment, and problem-solving. By analyzing how language models handle these challenges, researchers can gain insights into their reasoning processes and potential biases.

OpenVoiceChat is an open-source tool designed for having natural voice conversations with an LLM model. It supports various speech-to-text (STT), text-to-speech (TTS), and large language model (LLM) models. The tool aims to provide an alternative to closed commercial implementations, with well-abstracted APIs that are easy to use and extend. Users can install base and functionality-specific packages using pip, and the tool supports interruptions during conversations. The project encourages contributions through bounties and has a detailed roadmap available for reference.

This repository is a collection of resources focused on interpretability in large language models (LLMs). It aims to help beginners get started in the area and keep researchers updated on the latest progress. It includes libraries, blogs, tutorials, forums, tools, programs, papers, and more related to interpretability in LLMs.

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).

ChatAFL is a protocol fuzzer guided by large language models (LLMs) that extracts machine-readable grammar for protocol mutation, increases message diversity, and breaks coverage plateaus. It integrates with ProfuzzBench for stateful fuzzing of network protocols, providing smooth integration. The artifact includes modified versions of AFLNet and ProfuzzBench, source code for ChatAFL with proposed strategies, and scripts for setup, execution, analysis, and cleanup. Users can analyze data, construct plots, examine LLM-generated grammars, enriched seeds, and state-stall responses, and reproduce results with downsized experiments. Customization options include modifying fuzzers, tuning parameters, adding new subjects, troubleshooting, and working on GPT-4. Limitations include interaction with OpenAI's Large Language Models and a hard limit of 150,000 tokens per minute.

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.

Inspectus is a versatile visualization tool for large language models. It provides multiple views, including Attention Matrix, Query Token Heatmap, Key Token Heatmap, and Dimension Heatmap, to offer insights into language model behaviors. Users can interact with the tool in Jupyter notebooks through an easy-to-use Python API. Inspectus allows users to visualize attention scores between tokens, analyze how tokens focus on each other during processing, and explore the relationships between query and key tokens. The tool supports the visualization of attention maps from Huggingface transformers and custom attention maps, making it a valuable resource for researchers and developers working with language models.

LLMonFHIR is an iOS application that utilizes large language models (LLMs) to interpret and provide context around patient data in the Fast Healthcare Interoperability Resources (FHIR) format. It connects to the OpenAI GPT API to analyze FHIR resources, supports multiple languages, and allows users to interact with their health data stored in the Apple Health app. The app aims to simplify complex health records, provide insights, and facilitate deeper understanding through a conversational interface. However, it is an experimental app for informational purposes only and should not be used as a substitute for professional medical advice. Users are advised to verify information provided by AI models and consult healthcare professionals for personalized advice.

ContextCite is a tool for attributing statements generated by LLMs back to specific parts of the context. It allows users to analyze and understand the sources of information used by language models in generating responses. By providing attributions, users can gain insights into how the model makes decisions and where the information comes from.

This repository evaluates Large Language Models (LLMs) trained on PGN format chess games using linear probes. It assesses the LLMs' internal understanding of board state and their ability to estimate player skill levels. The repo provides tools to train, evaluate, and visualize linear probes on LLMs trained to play chess with PGN strings. Users can visualize the model's predictions, perform interventions on the model's internal board state, and analyze board state and player skill level accuracy across different LLMs. The experiments in the repo can be conducted with less than 1 GB of VRAM, and training probes on the 8 layer model takes about 10 minutes on an RTX 3050. The repo also includes scripts for performing board state interventions and skill interventions, along with useful links to open-source code, models, datasets, and pretrained models.

The Looker GenAI Extension provides code examples and resources for building a Looker Extension that integrates with Vertex AI Large Language Models (LLMs). Users can leverage the power of LLMs to enhance data exploration and analysis within Looker. The extension offers generative explore functionality to ask natural language questions about data and generative insights on dashboards to analyze data by asking questions. It leverages components like BQML Remote Models, BQML Remote UDF with Vertex AI, and Custom Fine Tune Model for different integration options. Deployment involves setting up infrastructure with Terraform and deploying the Looker Extension by creating a Looker project, copying extension files, configuring BigQuery connection, connecting to Git, and testing the extension. Users can save example prompts and configure user settings for the extension. Development of the Looker Extension environment includes installing dependencies, starting the development server, and building for production.

QMedia is an open-source multimedia AI content search engine designed specifically for content creators. It provides rich information extraction methods for text, image, and short video content. The tool integrates unstructured text, image, and short video information to build a multimodal RAG content Q&A system. Users can efficiently search for image/text and short video materials, analyze content, provide content sources, and generate customized search results based on user interests and needs. QMedia supports local deployment for offline content search and Q&A for private data. The tool offers features like content cards display, multimodal content RAG search, and pure local multimodal models deployment. Users can deploy different types of models locally, manage language models, feature embedding models, image models, and video models. QMedia aims to spark new ideas for content creation and share AI content creation concepts in an open-source manner.

LangWatch is a monitoring and analytics platform designed to track, visualize, and analyze interactions with Large Language Models (LLMs). It offers real-time telemetry to optimize LLM cost and latency, a user-friendly interface for deep insights into LLM behavior, user analytics for engagement metrics, detailed debugging capabilities, and guardrails to monitor LLM outputs for issues like PII leaks and toxic language. The platform supports OpenAI and LangChain integrations, simplifying the process of tracing LLM calls and generating API keys for usage. LangWatch also provides documentation for easy integration and self-hosting options for interested users.

Large Language Models Play StarCraft II is a project that explores the capabilities of large language models (LLMs) in playing the game StarCraft II. The project introduces TextStarCraft II, a textual environment for the game, and a Chain of Summarization method for analyzing game information and making strategic decisions. Through experiments, the project demonstrates that LLM agents can defeat the built-in AI at a challenging difficulty level. The project provides benchmarks and a summarization approach to enhance strategic planning and interpretability in StarCraft II gameplay.

Hands-On Large Language Models is a repository containing code examples from the book 'The Illustrated LLM Book' by Jay Alammar and Maarten Grootendorst. The repository provides practical tools and concepts for using Large Language Models with over 250 custom-made figures. It covers topics such as language model introduction, tokens and embeddings, transformer LLMs, text classification, text clustering, prompt engineering, text generation techniques, semantic search, multimodal LLMs, text embedding models, fine-tuning representation models, and fine-tuning generation models. The examples are designed to be run on Google Colab with T4 GPU support, but can be adapted to other cloud platforms as well.

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