Best AI tools for< Token Classification >

Token Counter is an AI tool designed to convert text input into tokens for various AI models. It helps users accurately determine the token count and associated costs when working with AI models. By providing insights into tokenization strategies and cost structures, Token Counter streamlines the process of utilizing advanced technologies.

The LLM Token Counter is a sophisticated tool designed to help users effectively manage token limits for various Language Models (LLMs) like GPT-3.5, GPT-4, Claude-3, Llama-3, and more. It utilizes Transformers.js, a JavaScript implementation of the Hugging Face Transformers library, to calculate token counts client-side. The tool ensures data privacy by not transmitting prompts to external servers.

GPT Calculator is a free tool that helps you calculate the token count and cost of your GPT prompts. You can also use the API to integrate the calculator into your own applications. GPT Calculator is a valuable tool for anyone who uses GPT-3 or other large language models.

NTM.ai is an AI-powered platform that provides tools and services for the cryptocurrency market. It offers features such as presales contract scanning, project listing, price tracking, and market analysis. The platform aims to assist users in making informed decisions and maximizing their investments in the volatile crypto market.

RejuveAI is a decentralized token-based system that aims to democratize longevity globally. The Longevity App allows users to take control of their health data, monitor essential metrics, and earn RJV tokens. The application leverages revolutionary AI technology to analyze human body functions in-depth, providing insights for combating aging. RejuveAI collaborates with researchers, clinics, and data enthusiasts to ensure affordable and accessible innovative outcomes. Users can unlock exclusive discounts on various services by accumulating RJV tokens.

GPTSidekick is an affordable GPT-4 powered AI assistant that can help you with a variety of tasks, including writing, coding, research, and more. It is easy to use and can be accessed from any device with an internet connection.

Laika AI is the world's first Web3-modeled AI ecosystem, designed and optimized for Web3 and blockchain. It offers advanced on-chain AI tools, integrating artificial intelligence and blockchain data to provide users with insights into the crypto landscape. Laika AI stands out with its user-friendly browser extension that empowers users with advanced on-chain analytics without the need for complex setups. The platform continuously learns and improves, leveraging a unique foundation and proprietary algorithms dedicated to Web3. Laika AI offers features such as DeFi research, token contract analysis, wallet insights, AI alerts, and multichain swap capabilities. It is supported by strategic partnerships with leading companies in the Web3 and Web2 space, ensuring security, high performance, and accessibility for users.

ChatX is a free prompt marketplace that offers ChatGPT, DALL·E, Stable Diffusion, and Midjourney AI tools. It provides a platform for users to easily find generative AI prompts for their projects, helping to enhance creativity and productivity. The marketplace also offers a variety of AI-inspired gifts and products for individuals passionate about AI.

CHAPTR is an innovative AI solutions provider that aims to redefine work and fuel human innovation. They offer AI-driven solutions tailored to empower, innovate, and transform work processes. Their products are designed to enhance efficiency, foster creativity, and anticipate change in the modern workforce. CHAPTR's solutions are user-centric, secure, customizable, and backed by the Holtzbrinck Publishing Group. They are committed to relentless innovation and continuous advancement in AI technology.

Deckee.AI is an AI-powered platform that allows users to instantly build blockchain websites and tokens. With Deckee.AI, users can create customized webpages for blogging, consulting, digital creation, and more. Deckee.AI also provides powerful editing tools, domain and SSL, separate hosting options, and the ability to choose the exact layout users want. Additionally, Deckee.AI makes it easy to create professional designs and digital collections, as well as unique digital tokens as a representation of products, events, rewards, and more.

FACE AI is a pioneering token project that combines blockchain technology and artificial intelligence to revolutionize video production. It offers a suite of AI-powered tools that enable users to create high-quality videos with ease, including text-to-video, image-to-video, face singing, and dance image generation.

Zoo is an open source text-to-image playground powered by Replicate Code Memories. Users can create images by inputting text and utilizing the Replicate API token. It is a project from Replicate, allowing users to easily generate images from text.

Cupiee is an AI-powered emotion companion on Web3 that aims to support and relieve users' emotions. It offers features like creating personalized spaces, sharing feelings anonymously, earning rewards through activities, and using the CUPI token for transactions and NFT sales. The platform also includes a roadmap for future developments, such as chat with AI Pet, generative AI based on stories, and building a marketplace for NFT and AI Pet trading.

Idolly is an AI-powered creative platform that allows users to generate high-quality custom images instantly. It offers a range of innovative features such as Face Transfer, Mood Fusion, Embrace Diversity, and Re-Create, enabling users to unleash their creativity and bring their wildest dreams to life. Users can interact with the platform through daily missions and a referral program to enhance their experience. With the power of AI magic and token technology, Idolly empowers users to explore new frontiers of creativity and express themselves in unique ways.

FOXSY.AI is an AI application that combines robotics and AI to create fully autonomous humanoid robot soccer players. The project aims to achieve the RoboCup final goal of having a team of robots win a soccer game against the winner of the most recent World Cup. The $FOXSY token powers the implementation of robotics and AI research, enabling users to engage with the RoboCup mechanics for entertainment value. The application offers various tools and features for users to participate in online tournaments, customize players, and analyze game strategies.

Braintrust is an innovative user-owned talent network for companies, offering an all-in-one hiring solution with AI capabilities. The platform connects top tech, design, and marketing talent with leading enterprises, saving time and money for both clients and talent. Braintrust ensures quality by curating top-tier professionals and using AI to instantly match clients with the best candidates. With a focus on transparency and fairness, Braintrust empowers talent to keep 100% of their earnings and have control over the network through the BTRST token. The platform aims to revolutionize the future of work by providing a reliable and efficient marketplace for talent and companies to collaborate.

BlockSurvey is an AI-driven survey platform that enables users to create, analyze, and manage surveys with a focus on data privacy and ownership. The platform offers end-to-end encryption, AI survey creation and analysis features, anonymous surveys, token-gated forms, and white-label customization. BlockSurvey empowers users to collect actionable insights securely, protect their reputation, boost trust and credibility, elevate brand status, and engage respondents with immersive survey experiences. With a strong emphasis on privacy and user control, BlockSurvey is designed for Web3 companies and individuals seeking data security and integrity in survey solutions.

Awan LLM is an AI tool that offers an Unlimited Tokens, Unrestricted, and Cost-Effective LLM Inference API Platform for Power Users and Developers. It allows users to generate unlimited tokens, use LLM models without constraints, and pay per month instead of per token. The platform features an AI Assistant, AI Agents, Roleplay with AI companions, Data Processing, Code Completion, and Applications for profitable AI-powered applications.

AI Keywording is an AI-powered tool designed to streamline the process of image keywording and description generation. By utilizing advanced AI technology, the tool automatically analyzes uploaded images to produce accurate keywords, compelling descriptions, and metadata for efficient use on stock websites. With a user-friendly interface and a simple 5-step workflow, AI Keywording aims to save users time and enhance productivity in managing their image assets. The tool offers token-based pricing, ensuring fair and accessible rates based on actual usage. Emphasizing data security and confidentiality, AI Keywording prioritizes user trust by safeguarding uploaded images and ensuring their deletion after a set period.

Kolank is an AI tool that provides a unified API for accessing a wide range of Language Model Models (LLMs) and providers. It offers features such as model comparison based on price, latency, output, context, and throughput, OpenAI compatible API integration, transparency in tracking API calls and token expenditure, cost reduction by paying for performance, load balancing with fallbacks, and easy integration with preferred LLMs using Python, Javascript, and Curl.

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.

Spark NLP is a state-of-the-art Natural Language Processing library built on top of Apache Spark. It provides simple, performant, and accurate NLP annotations for machine learning pipelines that scale easily in a distributed environment. Spark NLP comes with 36000+ pretrained pipelines and models in more than 200+ languages. It offers tasks such as Tokenization, Word Segmentation, Part-of-Speech Tagging, Named Entity Recognition, Dependency Parsing, Spell Checking, Text Classification, Sentiment Analysis, Token Classification, Machine Translation, Summarization, Question Answering, Table Question Answering, Text Generation, Image Classification, Image to Text (captioning), Automatic Speech Recognition, Zero-Shot Learning, and many more NLP tasks. Spark NLP is the only open-source NLP library in production that offers state-of-the-art transformers such as BERT, CamemBERT, ALBERT, ELECTRA, XLNet, DistilBERT, RoBERTa, DeBERTa, XLM-RoBERTa, Longformer, ELMO, Universal Sentence Encoder, Llama-2, M2M100, BART, Instructor, E5, Google T5, MarianMT, OpenAI GPT2, Vision Transformers (ViT), OpenAI Whisper, and many more not only to Python and R, but also to JVM ecosystem (Java, Scala, and Kotlin) at scale by extending Apache Spark natively.

**deep** doctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and selected NLP tasks and provides an integrated framework for fine-tuning, evaluating and running models. For more specific text processing tasks use one of the many other great NLP libraries. **deep** doctection focuses on applications and is made for those who want to solve real world problems related to document extraction from PDFs or scans in various image formats. **deep** doctection provides model wrappers of supported libraries for various tasks to be integrated into pipelines. Its core function does not depend on any specific deep learning library. Selected models for the following tasks are currently supported: * Document layout analysis including table recognition in Tensorflow with **Tensorpack**, or PyTorch with **Detectron2**, * OCR with support of **Tesseract**, **DocTr** (Tensorflow and PyTorch implementations available) and a wrapper to an API for a commercial solution, * Text mining for native PDFs with **pdfplumber**, * Language detection with **fastText**, * Deskewing and rotating images with **jdeskew**. * Document and token classification with all LayoutLM models provided by the **Transformer library**. (Yes, you can use any LayoutLM-model with any of the provided OCR-or pdfplumber tools straight away!). * Table detection and table structure recognition with **table-transformer**. * There is a small dataset for token classification available and a lot of new tutorials to show, how to train and evaluate this dataset using LayoutLMv1, LayoutLMv2, LayoutXLM and LayoutLMv3. * Comprehensive configuration of **analyzer** like choosing different models, output parsing, OCR selection. Check this notebook or the docs for more infos. * Document layout analysis and table recognition now runs with **Torchscript** (CPU) as well and **Detectron2** is not required anymore for basic inference. * [**new**] More angle predictors for determining the rotation of a document based on **Tesseract** and **DocTr** (not contained in the built-in Analyzer). * [**new**] Token classification with **LiLT** via **transformers**. We have added a model wrapper for token classification with LiLT and added a some LiLT models to the model catalog that seem to look promising, especially if you want to train a model on non-english data. The training script for LayoutLM can be used for LiLT as well and we will be providing a notebook on how to train a model on a custom dataset soon. **deep** doctection provides on top of that methods for pre-processing inputs to models like cropping or resizing and to post-process results, like validating duplicate outputs, relating words to detected layout segments or ordering words into contiguous text. You will get an output in JSON format that you can customize even further by yourself. Have a look at the **introduction notebook** in the notebook repo for an easy start. Check the **release notes** for recent updates. **deep** doctection or its support libraries provide pre-trained models that are in most of the cases available at the **Hugging Face Model Hub** or that will be automatically downloaded once requested. For instance, you can find pre-trained object detection models from the Tensorpack or Detectron2 framework for coarse layout analysis, table cell detection and table recognition. Training is a substantial part to get pipelines ready on some specific domain, let it be document layout analysis, document classification or NER. **deep** doctection provides training scripts for models that are based on trainers developed from the library that hosts the model code. Moreover, **deep** doctection hosts code to some well established datasets like **Publaynet** that makes it easy to experiment. It also contains mappings from widely used data formats like COCO and it has a dataset framework (akin to **datasets** so that setting up training on a custom dataset becomes very easy. **This notebook** shows you how to do this. **deep** doctection comes equipped with a framework that allows you to evaluate predictions of a single or multiple models in a pipeline against some ground truth. Check again **here** how it is done. Having set up a pipeline it takes you a few lines of code to instantiate the pipeline and after a for loop all pages will be processed through the pipeline.

LLM2Vec is a simple recipe to convert decoder-only LLMs into text encoders. It consists of 3 simple steps: 1) enabling bidirectional attention, 2) training with masked next token prediction, and 3) unsupervised contrastive learning. The model can be further fine-tuned to achieve state-of-the-art performance.

PostgresML is a powerful Postgres extension that seamlessly combines data storage and machine learning inference within your database. It enables running machine learning and AI operations directly within PostgreSQL, leveraging GPU acceleration for faster computations, integrating state-of-the-art large language models, providing built-in functions for text processing, enabling efficient similarity search, offering diverse ML algorithms, ensuring high performance, scalability, and security, supporting a wide range of NLP tasks, and seamlessly integrating with existing PostgreSQL tools and client libraries.

LLMLingua is a tool that utilizes a compact, well-trained language model to identify and remove non-essential tokens in prompts. This approach enables efficient inference with large language models, achieving up to 20x compression with minimal performance loss. The tool includes LLMLingua, LongLLMLingua, and LLMLingua-2, each offering different levels of prompt compression and performance improvements for tasks involving large language models.

Cleanlab helps you **clean** data and **lab** els by automatically detecting issues in a ML dataset. To facilitate **machine learning with messy, real-world data** , this data-centric AI package uses your _existing_ models to estimate dataset problems that can be fixed to train even _better_ models.

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.

PaddleNLP is an easy-to-use and high-performance NLP library. It aggregates high-quality pre-trained models in the industry and provides out-of-the-box development experience, covering a model library for multiple NLP scenarios with industry practice examples to meet developers' flexible customization needs.

FastFit is a Python package designed for fast and accurate few-shot classification, especially for scenarios with many semantically similar classes. It utilizes a novel approach integrating batch contrastive learning and token-level similarity score, significantly improving multi-class classification performance in speed and accuracy across various datasets. FastFit provides a convenient command-line tool for training text classification models with customizable parameters. It offers a 3-20x improvement in training speed, completing training in just a few seconds. Users can also train models with Python scripts and perform inference using pretrained models for text classification tasks.

Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for popular models like FlagEmbedding, Ember, GTE, and E5. It implements features such as no model graph compilation step, Metal support for local execution on Macs, small docker images with fast boot times, token-based dynamic batching, optimized transformers code for inference using Flash Attention, Candle, and cuBLASLt, Safetensors weight loading, and production-ready features like distributed tracing with Open Telemetry and Prometheus metrics.

This repository provides an LLM-driven audio codec model, LLM-Codec, for building multi-modal LLMs (text and audio modalities). The model enables frozen LLMs to achieve multiple audio tasks in a few-shot style without parameter updates. It compresses the audio modality into a well-trained LLMs token space, treating audio representation as a 'foreign language' that LLMs can learn with minimal examples. The proposed approach supports tasks like speech emotion classification, audio classification, text-to-speech generation, speech enhancement, etc., demonstrating feasibility and effectiveness in simple scenarios. The LLM-Codec model is open-sourced to facilitate research on few-shot audio task learning and multi-modal LLMs.

The Clarifai Python SDK offers a comprehensive set of tools to integrate Clarifai's AI platform to leverage computer vision capabilities like classification , detection ,segementation and natural language capabilities like classification , summarisation , generation , Q&A ,etc into your applications. With just a few lines of code, you can leverage cutting-edge artificial intelligence to unlock valuable insights from visual and textual content.

Detoxify is a library that provides trained models and code to predict toxic comments on 3 Jigsaw challenges: Toxic comment classification, Unintended Bias in Toxic comments, Multilingual toxic comment classification. It includes models like 'original', 'unbiased', and 'multilingual' trained on different datasets to detect toxicity and minimize bias. The library aims to help in stopping harmful content online by interpreting visual content in context. Users can fine-tune the models on carefully constructed datasets for research purposes or to aid content moderators in flagging out harmful content quicker. The library is built to be user-friendly and straightforward to use.

Semantic Cache is a tool for caching natural text based on semantic similarity. It allows for classifying text into categories, caching AI responses, and reducing API latency by responding to similar queries with cached values. The tool stores cache entries by meaning, handles synonyms, supports multiple languages, understands complex queries, and offers easy integration with Node.js applications. Users can set a custom proximity threshold for filtering results. The tool is ideal for tasks involving querying or retrieving information based on meaning, such as natural language classification or caching AI responses.

InternVL scales up the ViT to _**6B parameters**_ and aligns it with LLM. It is a vision-language foundation model that can perform various tasks, including: **Visual Perception** - Linear-Probe Image Classification - Semantic Segmentation - Zero-Shot Image Classification - Multilingual Zero-Shot Image Classification - Zero-Shot Video Classification **Cross-Modal Retrieval** - English Zero-Shot Image-Text Retrieval - Chinese Zero-Shot Image-Text Retrieval - Multilingual Zero-Shot Image-Text Retrieval on XTD **Multimodal Dialogue** - Zero-Shot Image Captioning - Multimodal Benchmarks with Frozen LLM - Multimodal Benchmarks with Trainable LLM - Tiny LVLM InternVL has been shown to achieve state-of-the-art results on a variety of benchmarks. For example, on the MMMU image classification benchmark, InternVL achieves a top-1 accuracy of 51.6%, which is higher than GPT-4V and Gemini Pro. On the DocVQA question answering benchmark, InternVL achieves a score of 82.2%, which is also higher than GPT-4V and Gemini Pro. InternVL is open-sourced and available on Hugging Face. It can be used for a variety of applications, including image classification, object detection, semantic segmentation, image captioning, and question answering.

Apollo is a multilingual medical LLM that covers English, Chinese, French, Hindi, Spanish, Hindi, and Arabic. It is designed to democratize medical AI to 6B people. Apollo has achieved state-of-the-art results on a variety of medical NLP tasks, including question answering, medical dialogue generation, and medical text classification. Apollo is easy to use and can be integrated into a variety of applications, making it a valuable tool for healthcare professionals and researchers.

The repository 'LLM-for-Healthcare' provides a comprehensive survey of large language models (LLMs) for healthcare, covering data, technology, applications, and accountability and ethics. It includes information on various LLM models, training data, evaluation methods, and computation costs. The repository also discusses tasks such as NER, text classification, question answering, dialogue systems, and generation of medical reports from images in the healthcare domain.

The Chinese LLM Benchmark is a continuous evaluation list of large models in CLiB, covering a wide range of commercial and open-source models from various companies and research institutions. It supports multidimensional evaluation of capabilities including classification, information extraction, reading comprehension, data analysis, Chinese encoding efficiency, and Chinese instruction compliance. The benchmark not only provides capability score rankings but also offers the original output results of all models for interested individuals to score and rank themselves.

Superpipe is a lightweight framework designed for building, evaluating, and optimizing data transformation and data extraction pipelines using LLMs. It allows users to easily combine their favorite LLM libraries with Superpipe's building blocks to create pipelines tailored to their unique data and use cases. The tool facilitates rapid prototyping, evaluation, and optimization of end-to-end pipelines for tasks such as classification and evaluation of job departments based on work history. Superpipe also provides functionalities for evaluating pipeline performance, optimizing parameters for cost, accuracy, and speed, and conducting grid searches to experiment with different models and prompts.

Expert in designing sustainable token economies.

A witty, crypto-savvy GPT for token securities insights, balancing humor and professionalism.

ERC20 analyst focusing on mintability, holders, LP tokens, and risks, with clear, conversational explanations.

Guides on ERC-20 token creation

Advisor on Security Token Offerings, providing insights without financial advice. Powered by Magic Circle

Smart Contract & Token Creation Wizard

Enhance D&D campaigns with Roll20 setup and custom token creation.

This GPT, combined into the 'STO-Platform', is designed to share expertise in total token offering (STO).㉿㉿

Guides users through creating Solana tokens from scratch with detailed explanations.

Build on the XRP Ledger with assistance from this GPT trained on extensive documentation and code samples.

The assistant launched by ChainBot.io can help you analyze EVM transactions, providing blockchain and crypto info.

Real-time Ethereum Blockchain Data & Insights (with Etherscan.io)

Specialist in cryptocurrency airdrops, providing info and claiming assistance.

A guide for building healthy relationships

From @cure4hayley - A comprehensive exploration of words and phrases. Includes composite word fusion and emotion-focused. Can also try film, TV and book titles. Enjoy!

Dominating the battlefield with every heart taken.

Powered by GPT-4 Turbo. 128,000 Tokens. Knowledge base of Discrete Math concepts, proofs and terminology. This GPT is instructed to carefully read and understand the prompt, plan a strategy to solve the problem, and write formal mathematical proofs.

Train monsters, travel the world, earn Arena Tokens and become the ultimate monster battling champion of earth!

Crypto Co-Pilot: Elevate Your Crypto Journey! 🚀 Get instant insights on trending tokens, uncover hidden gems, and access the latest crypto news. Your go-to chatbot for savvy trading and crypto discoveries. Let's navigate the crypto market together! 💎📈

Uniswap V3 dev helper with clear code and math explanations.