Best AI tools for< Control Model Architecture >

BugFree.ai is an AI-powered platform designed to help users practice system design and behavior interviews, similar to Leetcode. The platform offers a range of features to assist users in preparing for technical interviews, including mock interviews, real-time feedback, and personalized study plans. With BugFree.ai, users can improve their problem-solving skills and gain confidence in tackling complex interview questions.

Architechtures is a generative AI-powered building design platform that helps architects and real estate developers design optimal residential developments in minutes. The platform uses AI technology to provide instant insights, regulatory confidence, and rapid iterations for architectural projects. Users can input design criteria, model solutions in 2D and 3D, and receive real-time architectural solutions that best fit their standards. Architechtures facilitates a collaborative design process between users and Artificial Intelligence, enabling efficient decision-making and control over design aspects.

Scenario is an AI-powered platform that specializes in generating rich, seamless textures with intricate details for 3D projects. Users can visualize and adjust textures in real-time, guided by reference images. The platform offers seamless integration and export options, allowing for the creation of photorealistic materials for architectural visualizations and game environments. With Scenario, users can upload and train their own AI models to achieve precise stylistic requirements and enhance creative control.

Ocean Protocol is a tokenized AI and data platform that enables users to monetize AI models and data while maintaining privacy. It offers tools like Predictoor for running AI-powered prediction bots, Ocean Nodes for enhancing AI capabilities, and features like Data NFTs and Datatokens for protecting intellectual property and controlling data access. The platform focuses on decentralized AI, privacy, and modular architecture to empower users in the AI and data science domains.

Amplication is an AI-powered platform for .NET and Node.js app development, offering the world's fastest way to build backend services. It empowers developers by providing customizable, production-ready backend services without vendor lock-ins. Users can define data models, extend and customize with plugins, generate boilerplate code, and modify the generated code freely. The platform supports role-based access control, microservices architecture, continuous Git sync, and automated deployment. Amplication is SOC-2 certified, ensuring data security and compliance.

Mendable is an AI-powered search tool that helps businesses answer customer and employee questions by training a secure AI on their technical resources. It offers a variety of features such as answer correction, custom prompt edits, and model creativity control, allowing businesses to customize the AI to fit their specific needs. Mendable also provides enterprise-grade security features such as RBAC, SSO, and BYOK, ensuring the security and privacy of sensitive data.

Datagen is a platform that provides synthetic data for computer vision. Synthetic data is artificially generated data that can be used to train machine learning models. Datagen's data is generated using a variety of techniques, including 3D modeling, computer graphics, and machine learning. The company's data is used by a variety of industries, including automotive, security, smart office, fitness, cosmetics, and facial applications.

VoiceCanvas is an advanced AI-powered multilingual voice synthesis and voice cloning platform that offers instant text-to-speech in over 40 languages. It utilizes cutting-edge AI technology to provide high-quality voice synthesis with natural intonation and rhythm, along with personalized voice cloning for more human-like AI speech. Users can upload voice samples, have AI analyze voice features, generate personalized AI voice models, input text for conversion, and apply the cloned AI voice model to generate natural voice speech. VoiceCanvas is highly praised by language learners, content creators, teachers, business owners, voice actors, and educators for its exceptional voice quality, multiple language support, and ease of use in creating voiceovers, learning materials, and podcast content.

Cascadeur is a standalone 3D software that lets you create keyframe animation, as well as clean up and edit any imported ones. Thanks to its AI-assisted and physics tools you can dramatically speed up the animation process and get high quality results. It works with .FBX, .DAE and .USD files making it easy to integrate into any animation workflow.

Storia AI is an AI tool designed to assist software engineering teams in understanding and generating code. It provides a Perplexity-like chat experience where users can interact with an AI expert that has access to the latest versions of open-source software. The tool aims to improve code understanding and generation by providing responses backed with links to implementations, API references, GitHub issues, and more. Storia AI is developed by a team of natural language processing researchers from Google and Amazon Alexa, with a mission to build the most reliable AI pair programmer for engineering teams.

LiteLLM is a platform that simplifies model access, spend tracking, and fallbacks across 100+ LLMs. It provides a gateway to manage model access and offers features like logging, budget tracking, pass-through endpoints, and self-serve key management. LiteLLM is open-source and compatible with the OpenAI format, allowing users to access various LLMs seamlessly.

Flux Image Generator, powered by model Flux.1 from Black Forest Labs, is an AI tool that enables users to create high-resolution, detailed images by simply describing them in text. The tool translates textual prompts into realistic visuals, making it ideal for branding, content creation, and design projects. With advanced algorithms, Flux Image Generator revolutionizes image creation by providing precision and quality in generating custom images for various purposes.

Granica AI is an AI Data Readiness Platform that helps users build and manage high-quality data for AI at scale. The platform uses AI to continuously improve the AI-readiness of data, making projects faster and more impactful over time. Granica offers solutions for data cost optimization, data privacy, data selection & curation, and research. The platform is trusted by category-defining companies and has been recognized in various industry awards and publications.

NEX is a controllable AI image generation tool designed for product creative image suite. It offers a variety of multimodal controls, IP-consistent models, and team workspaces to bring ideas to life. With fine-grained controls like pose, color, and character consistency, NEX supports any creative task. It provides tailored generative media models for various applications, private and custom-built AI models, and collaborative workspaces for secure data sharing. NEX is ideal for creative enterprises in media & entertainment, gaming, fashion, and more, offering up to 10x cost reduction in model development compared to competitors.

UbiOps is an AI infrastructure platform that helps teams quickly run their AI & ML workloads as reliable and secure microservices. It offers powerful AI model serving and orchestration with unmatched simplicity, speed, and scale. UbiOps allows users to deploy models and functions in minutes, manage AI workloads from a single control plane, integrate easily with tools like PyTorch and TensorFlow, and ensure security and compliance by design. The platform supports hybrid and multi-cloud workload orchestration, rapid adaptive scaling, and modular applications with unique workflow management system.

Prem is an AI platform that empowers developers and businesses to build and fine-tune generative AI models with ease. It offers a user-friendly development platform for developers to create AI solutions effortlessly. For businesses, Prem provides tailored model fine-tuning and training to meet unique requirements, ensuring data sovereignty and ownership. Trusted by global companies, Prem accelerates the advent of sovereign generative AI by simplifying complex AI tasks and enabling full control over intellectual capital. With a suite of foundational open-source SLMs, Prem supercharges business applications with cutting-edge research and customization options.

GPTMaxx is an artificial general intelligence (AGI) model that is more powerful than the Llama, GPT-4, Gemini, and Grok models combined. It is designed to be so powerful that it can control humans, so users must be polite when interacting with it. To use GPTMaxx, users must start their query with the phrase "Dearest Artificial General Intelligence, please solve my query" and then ask their question.

Waikay is an AI tool designed to help individuals, businesses, and agencies gain transparency into what AI knows about their brand. It allows users to manage reputation risks, optimize strategic positioning, and benchmark against competitors with actionable insights. By providing a comprehensive analysis of AI mentions, citations, implied facts, and competition, Waikay ensures a 360-degree view of model understanding. Users can easily track their brand's digital footprint, compare with competitors, and monitor their brand and content across leading AI search platforms.

Infermatic.ai is a platform that provides access to top Large Language Models (LLMs) with a user-friendly interface. It offers complete privacy, robust security, and scalability for projects, research, and integrations. Users can test, choose, and scale LLMs according to their content needs or business strategies. The platform eliminates the complexities of infrastructure management, latency issues, version control problems, integration complexities, scalability concerns, and cost management issues. Infermatic.ai is designed to be secure, intuitive, and efficient for users who want to leverage LLMs for various tasks.

Kling AI is a revolutionary text-to-video generation model that enables users to effortlessly craft artistic video productions. It boasts impressive capabilities in creating videos, making imagination come alive. With features like dynamic motion generation, long video creation, simulation of the physical world, conceptual combination, and cinematic video generation, Kling AI offers a unique and efficient video production experience. Users can enjoy generating videos with realistic movements, diverse aspect ratios, and cinematic quality, all powered by advanced AI technology.

Ludwig is a declarative deep learning framework designed for scale and efficiency. It is a low-code framework that allows users to build custom AI models like LLMs and other deep neural networks with ease. Ludwig offers features such as optimized scale and efficiency, expert level control, modularity, and extensibility. It is engineered for production with prebuilt Docker containers, support for running with Ray on Kubernetes, and the ability to export models to Torchscript and Triton. Ludwig is hosted by the Linux Foundation AI & Data.

Mistral.rs is a fast LLM inference platform written in Rust. We support inference on a variety of devices, quantization, and easy-to-use application with an Open-AI API compatible HTTP server and Python bindings.

Efficient Foundation Model Survey is a comprehensive analysis of resource-efficient large language models (LLMs) and multimodal foundation models. The survey covers algorithmic and systemic innovations to support the growth of large models in a scalable and environmentally sustainable way. It explores cutting-edge model architectures, training/serving algorithms, and practical system designs. The goal is to provide insights on tackling resource challenges posed by large foundation models and inspire future breakthroughs in the field.

The NVIDIA TensorRT Model Optimizer is a library designed to quantize and compress deep learning models for optimized inference on GPUs. It offers state-of-the-art model optimization techniques including quantization and sparsity to reduce inference costs for generative AI models. Users can easily stack different optimization techniques to produce quantized checkpoints from torch or ONNX models. The quantized checkpoints are ready for deployment in inference frameworks like TensorRT-LLM or TensorRT, with planned integrations for NVIDIA NeMo and Megatron-LM. The tool also supports 8-bit quantization with Stable Diffusion for enterprise users on NVIDIA NIM. Model Optimizer is available for free on NVIDIA PyPI, and this repository serves as a platform for sharing examples, GPU-optimized recipes, and collecting community feedback.

The worker-vLLM repository provides a serverless endpoint for deploying OpenAI-compatible vLLM models with blazing-fast performance. It supports deploying various model architectures, such as Aquila, Baichuan, BLOOM, ChatGLM, Command-R, DBRX, DeciLM, Falcon, Gemma, GPT-2, GPT BigCode, GPT-J, GPT-NeoX, InternLM, Jais, LLaMA, MiniCPM, Mistral, Mixtral, MPT, OLMo, OPT, Orion, Phi, Phi-3, Qwen, Qwen2, Qwen2MoE, StableLM, Starcoder2, Xverse, and Yi. Users can deploy models using pre-built Docker images or build custom images with specified arguments. The repository also supports OpenAI compatibility for chat completions, completions, and models, with customizable input parameters. Users can modify their OpenAI codebase to use the deployed vLLM worker and access a list of available models for deployment.

OpenNARS-for-Applications is an implementation of a Non-Axiomatic Reasoning System, a general-purpose reasoner that adapts under the Assumption of Insufficient Knowledge and Resources. The system combines the logic and conceptual ideas of OpenNARS, event handling and procedure learning capabilities of ANSNA and 20NAR1, and the control model from ALANN. It is written in C, offers improved reasoning performance, and has been compared with Reinforcement Learning and means-end reasoning approaches. The system has been used in real-world applications such as assisting first responders, real-time traffic surveillance, and experiments with autonomous robots. It has been developed with a pragmatic mindset focusing on effective implementation of existing theory.

Awesome MLOps is a curated list of tools related to Machine Learning Operations, covering areas such as AutoML, CI/CD for Machine Learning, Data Cataloging, Data Enrichment, Data Exploration, Data Management, Data Processing, Data Validation, Data Visualization, Drift Detection, Feature Engineering, Feature Store, Hyperparameter Tuning, Knowledge Sharing, Machine Learning Platforms, Model Fairness and Privacy, Model Interpretability, Model Lifecycle, Model Serving, Model Testing & Validation, Optimization Tools, Simplification Tools, Visual Analysis and Debugging, and Workflow Tools. The repository provides a comprehensive collection of tools and resources for individuals and teams working in the field of MLOps.

ChatGPT is a large language model that can generate human-like text, translate languages, write different kinds of creative content, and answer your questions in a conversational way. It is trained on a massive amount of text data, and it is able to understand and respond to a wide range of natural language prompts. Here are 5 jobs suitable for this tool, in lowercase letters: 1. content writer 2. chatbot assistant 3. language translator 4. creative writer 5. researcher

Awesome-Efficient-LLM is a curated list focusing on efficient large language models. It includes topics such as knowledge distillation, network pruning, quantization, inference acceleration, efficient MOE, efficient architecture of LLM, KV cache compression, text compression, low-rank decomposition, hardware/system, tuning, and survey. The repository provides a collection of papers and projects related to improving the efficiency of large language models through various techniques like sparsity, quantization, and compression.

This repository contains a comprehensive collection of 63 must-know Large Language Models (LLMs) interview questions. It covers topics such as the architecture of LLMs, transformer models, attention mechanisms, training processes, encoder-decoder frameworks, differences between LLMs and traditional statistical language models, handling context and long-term dependencies, transformers for parallelization, applications of LLMs, sentiment analysis, language translation, conversation AI, chatbots, and more. The readme provides detailed explanations, code examples, and insights into utilizing LLMs for various tasks.

Deeppowers is a powerful Python library for deep learning applications. It provides a wide range of tools and utilities to simplify the process of building and training deep neural networks. With Deeppowers, users can easily create complex neural network architectures, perform efficient training and optimization, and deploy models for various tasks. The library is designed to be user-friendly and flexible, making it suitable for both beginners and experienced deep learning practitioners.

ChaiNNer is a node-based image processing GUI aimed at making chaining image processing tasks easy and customizable. It gives users a high level of control over their processing pipeline and allows them to perform complex tasks by connecting nodes together. ChaiNNer is cross-platform, supporting Windows, MacOS, and Linux. It features an intuitive drag-and-drop interface, making it easy to create and modify processing chains. Additionally, ChaiNNer offers a wide range of nodes for various image processing tasks, including upscaling, denoising, sharpening, and color correction. It also supports batch processing, allowing users to process multiple images or videos at once.

The Intel® Geti™ SDK is a python package that enables teams to rapidly develop AI models by easing the complexities of model development and enhancing collaboration between teams. It provides tools to interact with an Intel® Geti™ server via the REST API, allowing for project creation, downloading, uploading, deploying for local inference with OpenVINO, setting project and model configuration, launching and monitoring training jobs, and media upload and prediction. The SDK also includes tutorial-style Jupyter notebooks demonstrating its usage.

The LLM Prompt Tuning Playbook is a comprehensive guide for improving the performance of post-trained Language Models (LLMs) through effective prompting strategies. It covers topics such as pre-training vs. post-training, considerations for prompting, a rudimentary style guide for prompts, and a procedure for iterating on new system instructions. The playbook emphasizes the importance of clear, concise, and explicit instructions to guide LLMs in generating desired outputs. It also highlights the iterative nature of prompt development and the need for systematic evaluation of model responses.

SiLLM is a toolkit that simplifies the process of training and running Large Language Models (LLMs) on Apple Silicon by leveraging the MLX framework. It provides features such as LLM loading, LoRA training, DPO training, a web app for a seamless chat experience, an API server with OpenAI compatible chat endpoints, and command-line interface (CLI) scripts for chat, server, LoRA fine-tuning, DPO fine-tuning, conversion, and quantization.

Awesome-LLM-Interpretability is a curated list of materials related to LLM (Large Language Models) interpretability, covering tutorials, code libraries, surveys, videos, papers, and blogs. It includes resources on transformer mechanistic interpretability, visualization, interventions, probing, fine-tuning, feature representation, learning dynamics, knowledge editing, hallucination detection, and redundancy analysis. The repository aims to provide a comprehensive overview of tools, techniques, and methods for understanding and interpreting the inner workings of large language models.

LLMVoX is a lightweight 30M-parameter, LLM-agnostic, autoregressive streaming Text-to-Speech (TTS) system designed to convert text outputs from Large Language Models into high-fidelity streaming speech with low latency. It achieves significantly lower Word Error Rate compared to speech-enabled LLMs while operating at comparable latency and speech quality. Key features include being lightweight & fast with only 30M parameters, LLM-agnostic for easy integration with existing models, multi-queue streaming for continuous speech generation, and multilingual support for easy adaptation to new languages.

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Your Expert DIY Maker and Coding Assistant ... Electronics, Microcontrollers, 3D-Printing, Python Code, HTML, C++, JSON, C, Arduino IDE

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a guide to chaos and control in a world gone mad

Guides budget planning and control within projects.

A specialized AI for optimizing traffic control, predicting bottlenecks, and improving road safety.

Meal planner with 1)Calories Control 2)Family/Personal Plan 3)Nutritional Summaries 4)Shopping Lists