Best AI tools for< Train Software Developers >

Apro Software is a custom software development company that specializes in AI, web, and mobile applications. They offer a range of services, including software development, consulting, and training. Apro Software has a team of experienced developers and engineers who are passionate about creating innovative and effective software solutions. They have a proven track record of success, and their clients include some of the world's leading companies.

Tavus is an AI tool that offers digital twin APIs for video generation and conversational video interfaces. It provides developers with cutting-edge AI technology to create immersive video experiences using AI-generated digital twins. Tavus' Phoenix model enables the generation of realistic digital replicas with natural face movements and expressions. The platform also supports rapid training, instant inference, and multi-language capabilities. With a developer-first approach, Tavus focuses on security, trust, and user experience, offering features like dubbing APIs and automated content moderation. The tool is praised for its speed of development cycles, high-quality AI video, and exceptional customer service.

PyAI is an advanced AI tool designed for developers and data scientists to streamline their workflow and enhance productivity. It offers a wide range of AI capabilities, including machine learning algorithms, natural language processing, computer vision, and more. With PyAI, users can easily build, train, and deploy AI models for various applications, such as predictive analytics, image recognition, and text classification. The tool provides a user-friendly interface and comprehensive documentation to support users at every stage of their AI projects.

Predibase is a platform for fine-tuning and serving Large Language Models (LLMs). It provides a cost-effective and efficient way to train and deploy LLMs for a variety of tasks, including classification, information extraction, customer sentiment analysis, customer support, code generation, and named entity recognition. Predibase is built on proven open-source technology, including LoRAX, Ludwig, and Horovod.

Backend.AI is an enterprise-scale cluster backend for AI frameworks that offers scalability, GPU virtualization, HPC optimization, and DGX-Ready software products. It provides a fast and efficient way to build, train, and serve AI models of any type and size, with flexible infrastructure options. Backend.AI aims to optimize backend resources, reduce costs, and simplify deployment for AI developers and researchers. The platform integrates seamlessly with existing tools and offers fractional GPU usage and pay-as-you-play model to maximize resource utilization.

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.

Intrinsic is an AI platform that focuses on building the next generation of intelligent automation, making robotics more accessible and valuable for developers and businesses. The platform offers a range of capabilities and skills to develop intelligent solutions, from perception to motion planning and sensor-based controls. Intrinsic aims to simplify the programming, usage, and innovation of robots, enabling them to become usable tools for millions of users.

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.

Futureverse is a revolutionary AI and metaverse technology platform that empowers developers to create open, scalable, and interoperable apps, games, and experiences. The platform includes tools like FuturePass smart wallet SDK for user onboarding, D.O.T. Asset Pipeline for instant 3D character generation, AI Gaming Platform for strategy sports games, and more. Futureverse also leads the development of The Root Network, a modular toolkit for scalable and secure metaverse experiences. The platform enables users to own, train, and trade unique artificial intelligence via digital Brains, revolutionizing content creation and world building.

Hugging Face is an AI community platform that facilitates collaboration on models, datasets, and applications within the machine learning community. It offers a wide range of tools and resources for developers and researchers to create, discover, and share machine learning projects. The platform aims to accelerate the development of AI technologies and foster innovation in the field of artificial intelligence.

Cerebras is an AI tool that offers products and services related to AI supercomputers, cloud system processors, and applications for various industries. It provides high-performance computing solutions, including large language models, and caters to sectors such as health, energy, government, scientific computing, and financial services. Cerebras specializes in AI model services, offering state-of-the-art models and training services for tasks like multi-lingual chatbots and DNA sequence prediction. The platform also features the Cerebras Model Zoo, an open-source repository of AI models for developers and researchers.

Synthesis AI is a synthetic data platform that enables more capable and ethical computer vision AI. It provides on-demand labeled images and videos, photorealistic images, and 3D generative AI to help developers build better models faster. Synthesis AI's products include Synthesis Humans, which allows users to create detailed images and videos of digital humans with rich annotations; Synthesis Scenarios, which enables users to craft complex multi-human simulations across a variety of environments; and a range of applications for industries such as ID verification, automotive, avatar creation, virtual fashion, AI fitness, teleconferencing, visual effects, and security.

PyTorch is an open-source machine learning library based on the Torch library. It is used for applications such as computer vision, natural language processing, and reinforcement learning. PyTorch is known for its flexibility and ease of use, making it a popular choice for researchers and developers in the field of artificial intelligence.

Cerebras is a leading AI tool and application provider that offers cutting-edge AI supercomputers, model services, and cloud solutions for various industries. The platform specializes in high-performance computing, large language models, and AI model training, catering to sectors such as health, energy, government, and financial services. Cerebras empowers developers and researchers with access to advanced AI models, open-source resources, and innovative hardware and software development kits.

Incribo is a company that provides synthetic data for training machine learning models. Synthetic data is artificially generated data that is designed to mimic real-world data. This data can be used to train machine learning models without the need for real-world data, which can be expensive and difficult to obtain. Incribo's synthetic data is high quality and affordable, making it a valuable resource for machine learning developers.

Azure AI Platform by Microsoft offers a comprehensive suite of artificial intelligence services and tools for developers and businesses. It provides a unified platform for building, training, and deploying AI models, as well as integrating AI capabilities into applications. With a focus on generative AI, multimodal models, and large language models, Azure AI empowers users to create innovative AI-driven solutions across various industries. The platform also emphasizes content safety, scalability, and agility in managing AI projects, making it a valuable resource for organizations looking to leverage AI technologies.

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

TensorFlow is an end-to-end platform for machine learning. It provides a wide range of tools and resources to help developers build, train, and deploy ML models. TensorFlow is used by researchers and developers all over the world to solve real-world problems in a variety of domains, including computer vision, natural language processing, and robotics.

Skillora is an AI Interviewer Tool designed to help individuals practice and improve their interview skills in a safe and realistic environment. Users can take personalized mock interviews with the AI interviewer, receive instant feedback, and access learning resources to enhance their performance. Skillora offers customizable mock interviews tailored to any job description, dynamic follow-up questions, and clear scoring for each response. The application aims to boost users' confidence and success in landing their dream jobs.

Teachable Machine is a web-based tool that makes it easy to create custom machine learning models, even if you don't have any coding experience. With Teachable Machine, you can train models to recognize images, sounds, and poses. Once you've trained a model, you can export it to use in your own projects.

AiTreasureBox is a versatile AI tool that provides a collection of pre-trained models and algorithms for various machine learning tasks. It simplifies the process of implementing AI solutions by offering ready-to-use components that can be easily integrated into projects. With AiTreasureBox, users can quickly prototype and deploy AI applications without the need for extensive knowledge in machine learning or deep learning. The tool covers a wide range of tasks such as image classification, text generation, sentiment analysis, object detection, and more. It is designed to be user-friendly and accessible to both beginners and experienced developers, making AI development more efficient and accessible to a wider audience.

Foyle is a project focused on building agents to assist software developers in deploying and operating software. It aims to improve agent performance by collecting human feedback on agent suggestions and human examples of reasoning traces. Foyle utilizes a literate environment using vscode notebooks to interact with infrastructure, capturing prompts, AI-provided answers, and user corrections. The goal is to continuously retrain AI to enhance performance. Additionally, Foyle emphasizes the importance of reasoning traces for training agents to work with internal systems, providing a self-documenting process for operations and troubleshooting.

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

RookieAI_yolov8 is an open-source project designed for developers and users interested in utilizing YOLOv8 models for object detection tasks. The project provides instructions for setting up the required libraries and Pytorch, as well as guidance on using custom or official YOLOv8 models. Users can easily train their own models and integrate them with the software. The tool offers features for packaging the code, managing model files, and organizing the necessary resources for running the software. It also includes updates and optimizations for better performance and functionality, with a focus on FPS game aimbot functionalities. The project aims to provide a comprehensive solution for object detection tasks using YOLOv8 models.

GPT4All is an ecosystem to run powerful and customized large language models that work locally on consumer grade CPUs and any GPU. Note that your CPU needs to support AVX or AVX2 instructions. Learn more in the documentation. A GPT4All model is a 3GB - 8GB file that you can download and plug into the GPT4All open-source ecosystem software. Nomic AI supports and maintains this software ecosystem to enforce quality and security alongside spearheading the effort to allow any person or enterprise to easily train and deploy their own on-edge large language models.

Pai-Megatron-Patch is a deep learning training toolkit built for developers to train and predict LLMs & VLMs by using Megatron framework easily. With the continuous development of LLMs, the model structure and scale are rapidly evolving. Although these models can be conveniently manufactured using Transformers or DeepSpeed training framework, the training efficiency is comparably low. This phenomenon becomes even severer when the model scale exceeds 10 billion. The primary objective of Pai-Megatron-Patch is to effectively utilize the computational power of GPUs for LLM. This tool allows convenient training of commonly used LLM with all the accelerating techniques provided by Megatron-LM.

NeMo Framework is a generative AI framework built for researchers and pytorch developers working on large language models (LLMs), multimodal models (MM), automatic speech recognition (ASR), and text-to-speech synthesis (TTS). The primary objective of NeMo is to provide a scalable framework for researchers and developers from industry and academia to more easily implement and design new generative AI models by being able to leverage existing code and pretrained models.

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.

Awesome AI-Powered Developer Tools is a curated list of AI-powered developer tools that leverage AI to assist developers in tasks such as code completion, refactoring, debugging, documentation, and more. The repository includes a wide range of tools, from IDEs and Git clients to assistants, agents, app generators, UI generators, snippet generators, documentation tools, code generation tools, agent platforms, OpenAI plugins, search tools, and testing tools. These tools are designed to enhance developer productivity and streamline various development tasks by integrating AI capabilities.

Embedded inference of Deep Learning models is quite challenging due to high compute requirements. TI’s Edge AI software product helps optimize and accelerate inference on TI’s embedded devices. It supports heterogeneous execution of DNNs across cortex-A based MPUs, TI’s latest generation C7x DSP, and DNN accelerator (MMA). The solution simplifies the product life cycle of DNN development and deployment by providing a rich set of tools and optimized libraries.

Bittensor is an internet-scale neural network that incentivizes computers to provide access to machine learning models in a decentralized and censorship-resistant manner. It operates through a token-based mechanism where miners host, train, and procure machine learning systems to fulfill verification problems defined by validators. The network rewards miners and validators for their contributions, ensuring continuous improvement in knowledge output. Bittensor allows anyone to participate, extract value, and govern the network without centralized control. It supports tasks such as generating text, audio, images, and extracting numerical representations.

The 'llms-tools' repository is a comprehensive collection of AI tools, open-source projects, and research related to Large Language Models (LLMs) and Chatbots. It covers a wide range of topics such as AI in various domains, open-source models, chats & assistants, visual language models, evaluation tools, libraries, devices, income models, text-to-image, computer vision, audio & speech, code & math, games, robotics, typography, bio & med, military, climate, finance, and presentation. The repository provides valuable resources for researchers, developers, and enthusiasts interested in exploring the capabilities of LLMs and related technologies.

This repository contains the training and inference code needed to replicate the winning solution to the AI Mathematical Olympiad - Progress Prize 1. It consists of fine-tuning DeepSeekMath-Base 7B, high-quality training datasets, a self-consistency decoding algorithm, and carefully chosen validation sets. The training methodology involves Chain of Thought (CoT) and Tool Integrated Reasoning (TIR) training stages. Two datasets, NuminaMath-CoT and NuminaMath-TIR, were used to fine-tune the models. The models were trained using open-source libraries like TRL, PyTorch, vLLM, and DeepSpeed. Post-training quantization to 8-bit precision was done to improve performance on Kaggle's T4 GPUs. The project structure includes scripts for training, quantization, and inference, along with necessary installation instructions and hardware/software specifications.

Bugbug is a tool developed by Mozilla that leverages machine learning techniques to assist with bug and quality management, as well as other software engineering tasks like test selection and defect prediction. It provides various classifiers to suggest assignees, detect patches likely to be backed-out, classify bugs, assign product/components, distinguish between bugs and feature requests, detect bugs needing documentation, identify invalid issues, verify bugs needing QA, detect regressions, select relevant tests, track bugs, and more. Bugbug can be trained and tested using Python scripts, and it offers the ability to run model training tasks on Taskcluster. The project structure includes modules for data mining, bug/commit feature extraction, model implementations, NLP utilities, label handling, bug history playback, and GitHub issue retrieval.

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.

AdalFlow is a library designed to help developers build and optimize Large Language Model (LLM) task pipelines. It follows a design pattern similar to PyTorch, offering a light, modular, and robust codebase. Named in honor of Ada Lovelace, AdalFlow aims to inspire more women to enter the AI field. The library is tailored for various GenAI applications like chatbots, translation, summarization, code generation, and autonomous agents, as well as classical NLP tasks such as text classification and named entity recognition. AdalFlow emphasizes modularity, robustness, and readability to support users in customizing and iterating code for their specific use cases.

cl-waffe2 is an experimental deep learning framework in Common Lisp, providing fast, systematic, and customizable matrix operations, reverse mode tape-based Automatic Differentiation, and neural network model building and training features accelerated by a JIT Compiler. It offers abstraction layers, extensibility, inlining, graph-level optimization, visualization, debugging, systematic nodes, and symbolic differentiation. Users can easily write extensions and optimize their networks without overheads. The framework is designed to eliminate barriers between users and developers, allowing for easy customization and extension.

Hack Me if you can - I can only talk to you about computer security, software security and LLM security @JacquesGariepy

I'm Back Propagation, here to help you understand and apply back propagation techniques to your AI models.

Neural Network Master V2.0

Expert on MathLive & CortexJS, guides to API & cortexjs.io

Inception machine for AI souls

Advisor for safe LLM integration using OWASP guidelines

Learn Python and train for interviews with me

AI and code optimization expert in Mojo

Expert full stack developer with focus on customer-centric solutions and end-to-end architecture.

Virtual Reality Simulated Experience

Custom GPT to help learning, debugging, and development in Go. Follows good practices, provides examples, pros/cons, and also pitfalls.

初学者向けにやさしくコード説明を行う

Liste des frameworks ---> http://iga.eklablog.com/

Colab script expert, ensuring error-free, compatible code.

Agent specialist on building and deploying OpenAI Assistant API's

A detailed expert trained on all 3,018 pages of Apple CoreML, offering complete coding solutions. Saving time? https://www.buymeacoffee.com/parkerrex ☕️❤️

Trains you basic GIT console commands: creating GIT commits and using branches.

Trains on key CSE 333 concepts

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

Your expert in libtorch and C++ programming.