Best AI tools for< Train On Specific Tasks >

Cody is an intelligent AI assistant designed to boost team productivity by providing instant answers, support, troubleshooting, and idea generation. It can be trained on your business knowledge base to cater to your specific needs, making it a valuable asset for various departments such as marketing, HR, IT support, business consultancy, creative tasks, sales, training, hiring, customer support, and translation. Cody offers features like prompt manager, focus mode, conversation logs, scratchpad, and source checking, ensuring efficient and tailored assistance. With multilingual capabilities and customizable access controls, Cody prioritizes data security and user experience.

Frame AI is a premier Streaming AI Platform powered by STAG, designed to provide proactive insights and tools for every team by continuously querying customer data to detect traits, track trends, and trigger workflows. The platform turns unstructured data into actionable insights, helping teams stay ahead of risks and opportunities. Frame AI's architecture autonomously queries customer data based on user objectives, activating inside existing business tools to provide real-time customer data. With features like enrichments, triggers, alerts, and insights, Frame AI enables better decisions faster by combining predictive signals in customer text into task-specific scores. The platform is suitable for marketing, CX, support, and product teams, offering real-time usability feedback, demographic and psychographic trait detection, and secure data handling. Frame AI is SOC 2 Type II certified and HIPAA compliant, with a team of AI experts leading the development of AI solutions for various organizations.

Lexy is an AI chatbot application designed to enhance customer service on websites. It integrates with Notion pages to provide instant, human-like answers to customer queries. Lexy can be set up in just 5 minutes, prioritizes data security, and can be trained on specific Notion pages. The application is free to create the first bot and send 30 messages per month, with options to upgrade for more power.

ChatCube is an AI-powered chatbot maker that allows users to create chatbots for their websites without coding. It uses advanced AI technology to train chatbots on any document or website within 60 seconds. ChatCube offers a range of features, including a user-friendly visual editor, lightning-fast integration, fine-tuning on specific data sources, data encryption and security, and customizable chatbots. By leveraging the power of AI, ChatCube helps businesses improve customer support efficiency and reduce support ticket reductions by up to 28%.

Vize.ai is a custom image recognition API provided by Ximilar, a leading company in Visual AI and Search. The tool offers powerful artificial intelligence capabilities with high accuracy using deep learning algorithms. It allows users to easily set up and implement cutting-edge vision automation without any development costs. Vize.ai enables users to train custom neural networks to recognize specific images and provides a scalable solution with continuous improvements in machine learning algorithms. The tool features an intuitive interface that requires no machine learning or coding knowledge, making it accessible for a wide range of users across industries.

Chatflot is an AI chatbot application that helps businesses automate up to 95% of customer queries. It allows users to create customized AI chatbots based on the ChatGPT language model, enabling them to provide on-demand information to customers through their website. Chatflot is suitable for various industries and offers features like training the chatbot on specific data, optimizing customer interactions, and integrating seamlessly with different CMS platforms. The application aims to enhance customer service, boost sales, and streamline support processes by providing personalized assistance and relevant information to users.

ChatGPT is an AI-powered chatbot tool that allows users to create and train chatbots for various purposes. It uses advanced natural language processing to generate human-like responses and engage in conversations with users. With ChatGPT, you can customize the chatbot's responses, train it on specific topics, and integrate it into your website or application to provide interactive and personalized experiences for your users.

Safurai is an AI-powered coding assistant that helps developers write code faster, safer, and better. It offers a range of features, including a textbox for asking questions and getting code suggestions, shortcuts for code optimization and unit testing, the ability to train the assistant on specific projects, and a natural language search for finding code. Safurai is compatible with various IDEs, including Visual Studio Code, IntelliJ, and PyCharm.

FoxyApps is a no-code platform that allows users to build, host, and monetize AI toolsets without the need for coding. Users can create AI tools targeting specific audiences, customize their portals, and monetize their creations through various payment providers. The platform offers a range of features including a no-code builder, white-label solutions, and powerful AI models sourced from reputable providers like OpenAI and Google.

RunPod is a cloud platform specifically designed for AI development and deployment. It offers a range of features to streamline the process of developing, training, and scaling AI models, including a library of pre-built templates, efficient training pipelines, and scalable deployment options. RunPod also provides access to a wide selection of GPUs, allowing users to choose the optimal hardware for their specific AI workloads.

Lamini is an enterprise-level LLM platform that offers precise recall with Memory Tuning, enabling teams to achieve over 95% accuracy even with large amounts of specific data. It guarantees JSON output and delivers massive throughput for inference. Lamini is designed to be deployed anywhere, including air-gapped environments, and supports training and inference on Nvidia or AMD GPUs. The platform is known for its factual LLMs and reengineered decoder that ensures 100% schema accuracy in the JSON output.

Passarel is an AI tool designed to simplify teammate onboarding by developing bespoke GPT-like models for employee interaction. It centralizes knowledge bases into a custom model, allowing new teammates to access information efficiently. Passarel leverages various integrations to tailor language models to team needs, handling contradictions and providing accurate information. The tool works by training models on chosen knowledge bases, learning from data and configurations provided, and deploying the model for team use.

Helix AI is a private GenAI platform that enables users to build AI applications using open source models. The platform offers tools for RAG (Retrieval-Augmented Generation) and fine-tuning, allowing deployment on-premises or in a Virtual Private Cloud (VPC). Users can access curated models, utilize Helix API tools to connect internal and external APIs, embed Helix Assistants into websites/apps for chatbot functionality, write AI application logic in natural language, and benefit from the innovative RAG system for Q&A generation. Additionally, users can fine-tune models for domain-specific needs and deploy securely on Kubernetes or Docker in any cloud environment. Helix Cloud offers free and premium tiers with GPU priority, catering to individuals, students, educators, and companies of varying sizes.

Prompteasy.ai is an AI tool that allows users to fine-tune AI models in less than 5 minutes. It simplifies the process of training AI models on user data, making it as easy as having a conversation. Users can fully customize GPT by fine-tuning it to meet their specific needs. The tool offers data-driven customization, interactive AI coaching, and seamless model enhancement, providing users with a competitive edge and simplifying AI integration into their workflows.

Signature AI is a private and specialized artificial intelligence platform designed to empower creative teams in content creation. It offers bespoke AI models for visual content creation, training domain-specific AI models, generating images from text descriptions, transforming media pipelines, and upscaling output images. The platform ensures privacy, safety, and security by using locally hosted Foundation Models and curated training data. It also focuses on scalability and flexibility, optimizing operations and budget impact for creative teams.

ioni.ai is an AI application that offers ChatGPT-4 solution for customer support. It is a smart chatbot based on the latest AI technology, designed to handle general inquiries, complex questions, and user-specific requests. The application streamlines workflow with immediate responses, brings CSAT scores to a new level, and ensures human-in-the-loop verification for quality control. With self-learning capabilities, ioni.ai constantly improves its responses and provides accurate solutions to customer inquiries.

ResumeWriting is an AI-powered platform that revolutionizes the resume writing process. With the help of GPT AI technology, users can create an ideal resume in just 3 minutes by describing their career briefly. The platform generates targeted resumes for specific job openings, allowing users to customize their resumes based on keywords and job requirements. Users can train the AI with their career history and easily tailor resumes for different job listings. ResumeWriting offers a simple 3-step process to generate, download, and edit/print resumes, providing users with multiple design options to choose from.

Support AI is a custom AI chatbot application powered by ChatGPT that allows website owners to create personalized chatbots to provide instant answers to customers, capture leads, and enhance customer support. With Support AI, users can easily integrate AI chatbots on their websites, train them with specific content, and customize their behavior and responses. The application offers features such as capturing leads, providing accurate answers, handling bookings, collecting feedback, and offering product recommendations. Users can choose from different pricing plans based on their message volume and training content needs.

Chunky is an AI chatbot builder that allows users to create human-like chatbots effortlessly. With Chunky, you can automate customer support, train your bot on your own data, and integrate it seamlessly into your website. The platform offers a user-friendly interface, fast and personal support, and a generous free forever plan. Chunky is powered by the ChatGPT API and Embeddings provided by OpenAI, supporting close to 95 languages for both training data and bot responses.

Botsonic is an AI chatbot application that offers custom AI chatbots for websites. It provides AI-powered automation solutions for various industries, enabling businesses to enhance customer engagement, support, sales, and more. Botsonic uses AI Copilots trained on data to deliver authentic customer experiences in multiple languages across different channels. The platform allows users to easily create, customize, and integrate AI chatbots into their websites, providing instant support and personalized interactions.

TRACE is a temporal grounding video model that utilizes causal event modeling to capture videos' inherent structure. It presents a task-interleaved video LLM model tailored for sequential encoding/decoding of timestamps, salient scores, and textual captions. The project includes various model checkpoints for different stages and fine-tuning on specific datasets. It provides evaluation codes for different tasks like VTG, MVBench, and VideoMME. The repository also offers annotation files and links to raw videos preparation projects. Users can train the model on different tasks and evaluate the performance based on metrics like CIDER, METEOR, SODA_c, F1, mAP, Hit@1, etc. TRACE has been enhanced with trace-retrieval and trace-uni models, showing improved performance on dense video captioning and general video understanding tasks.

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

LABO is a time series forecasting and analysis framework that integrates pre-trained and fine-tuned LLMs with multi-domain agent-based systems. It allows users to create and tune agents easily for various scenarios, such as stock market trend prediction and web public opinion analysis. LABO requires a specific runtime environment setup, including system requirements, Python environment, dependency installations, and configurations. Users can fine-tune their own models using LABO's Low-Rank Adaptation (LoRA) for computational efficiency and continuous model updates. Additionally, LABO provides a Python library for building model training pipelines and customizing agents for specific tasks.

This repository is a curated collection of resources for fine-tuning Large Language Models (LLMs) like GPT, BERT, RoBERTa, and their variants. It includes tutorials, papers, tools, frameworks, and best practices to aid researchers, data scientists, and machine learning practitioners in adapting pre-trained models to specific tasks and domains. The resources cover a wide range of topics related to fine-tuning LLMs, providing valuable insights and guidelines to streamline the process and enhance model performance.

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.

LitGPT is a command-line tool designed to easily finetune, pretrain, evaluate, and deploy 20+ LLMs **on your own data**. It features highly-optimized training recipes for the world's most powerful open-source large-language-models (LLMs).

**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.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

This project provides a comprehensive guide to fine-tuning large language models (LLMs) with efficient methods like LoRA and P-tuning V2. It includes detailed instructions, code examples, and performance benchmarks for various LLMs and fine-tuning techniques. The guide also covers data preparation, evaluation, prediction, and running inference on CPU environments. By leveraging this guide, users can effectively fine-tune LLMs for specific tasks and applications.

A curated list of data science & AI guided projects to start building your portfolio. The repository contains guided projects covering various topics such as large language models, time series analysis, computer vision, natural language processing (NLP), and data science. Each project provides detailed instructions on how to implement specific tasks using different tools and technologies.

Prometheus-Eval is a repository dedicated to evaluating large language models (LLMs) in generation tasks. It provides state-of-the-art language models like Prometheus 2 (7B & 8x7B) for assessing in pairwise ranking formats and achieving high correlation scores with benchmarks. The repository includes tools for training, evaluating, and using these models, along with scripts for fine-tuning on custom datasets. Prometheus aims to address issues like fairness, controllability, and affordability in evaluations by simulating human judgments and proprietary LM-based assessments.

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.

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.

Technical expert on locomotives, trains, signalling, and railway technology. Can answer questions and draw designs specific to transportation domain.

An expert chatbot on AR 600-20, Army Command Policy

I'm PhishCatcher, an expert in identifying phishing attempts.

Expert in web design & accessibility, offering assessments and development guidance.

Friendly train travel guide focusing on the best routes, essential travel information, and personalized travel insights, for both experienced and novice travelers.

Expert on ADA compliance, here to guide you through accessibility standards and regulations. ***Not legal advice.***

Expert on OSHA standards, ideal for safety professionals.

Expert on privacy laws: GDPR, CCPA, PIPEDA, U.S. state laws

Advises businesses on labor and employment law compliance.

Provides emergency training assistance with a focus on safety and clear guidelines.

ERP expert with a focus on Program Management, Business Analysis, and Systems Analysis utilizing Agile and PMBOK principles.

Clear, direct guidance on business ethics.

Learn what current and future leaders in communication think about AI's impact on our industry!

Expert in cyber security (NIST, OWASP, NIS2, MITRE ATT&CK, DORA) and GDPR, offering clear and concise guidance.

Promotes inclusive culture and diversity within the organization.

Assistant de conformité RGPD

Expert in HIPAA compliance for medical supplies

A safeguarding advisor for schools, aligned with 'Keeping Children Safe In Education' guidelines.

ISO27001およびISO/IEC 27002のベストプラクティスに精通したアドバイザー　Expert in ISO27001 and ISO/IEC 27002 best practices.

Expert in answering Employment Law queries for small businesses in the USA