Best AI tools for< Deploy Models Safely >

Dust is a customizable and secure AI assistant platform that helps businesses amplify their team's potential. It allows users to deploy the best Large Language Models to their company, connect Dust to their team's data, and empower their teams with assistants tailored to their specific needs. Dust is exceptionally modular and adaptable, tailoring to unique requirements and continuously evolving to meet changing needs. It supports multiple sources of data and models, including proprietary and open-source models from OpenAI, Anthropic, and Mistral. Dust also helps businesses identify their most creative and driven team members and share their experience with AI throughout the company. It promotes collaboration with shared conversations, @mentions in discussions, and Slackbot integration. Dust prioritizes security and data privacy, ensuring that data remains private and that enterprise-grade security measures are in place to manage data access policies.

OmniAI is an AI tool that allows teams to deploy AI applications on their existing infrastructure. It provides a unified API experience for building AI applications and offers a wide selection of industry-leading models. With tools like Llama 3, Claude 3, Mistral Large, and AWS Titan, OmniAI excels in tasks such as natural language understanding, generation, safety, ethical behavior, and context retention. It also enables users to deploy and query the latest AI models quickly and easily within their virtual private cloud environment.

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.

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.

Aify.co is a website that covers all things artificial intelligence. It provides news, analysis, and opinion on the latest developments in AI, as well as resources for developers and users. The site is written by a team of experts in AI, and it is committed to providing accurate and up-to-date information on the field.

Mystic.ai is an AI tool designed to deploy and scale Machine Learning models with ease. It offers a fully managed Kubernetes platform that runs in your own cloud, allowing users to deploy ML models in their own Azure/AWS/GCP account or in a shared GPU cluster. Mystic.ai provides cost optimizations, fast inference, simpler developer experience, and performance optimizations to ensure high-performance AI model serving. With features like pay-as-you-go API, cloud integration with AWS/Azure/GCP, and a beautiful dashboard, Mystic.ai simplifies the deployment and management of ML models for data scientists and AI engineers.

PoplarML is a platform that enables the deployment of production-ready, scalable ML systems with minimal engineering effort. It offers one-click deploys, real-time inference, and framework agnostic support. With PoplarML, users can seamlessly deploy ML models using a CLI tool to a fleet of GPUs and invoke their models through a REST API endpoint. The platform supports Tensorflow, Pytorch, and JAX models.

Outfit AI is an AI tool that enables users to design and deploy AI models or workflows as user-ready applications in minutes. It allows users to create custom user interfaces for their AI-powered apps by dropping in an API key from Replicate or Hugging Face. With Outfit AI, users can have creative control over the design of their apps, build complex workflows without any code, and optimize prompts for better performance. The tool aims to help users launch their models faster, save time, and enhance their AI applications with a built-in product copilot.

Groq is a fast AI inference tool that offers GroqCloud™ Platform and GroqRack™ Cluster for developers to build and deploy AI models with ultra-low-latency inference. It provides instant intelligence for openly-available models like Llama 3.1 and is known for its speed and compatibility with other AI providers. Groq powers leading openly-available AI models and has gained recognition in the AI chip industry. The tool has received significant funding and valuation, positioning itself as a strong challenger to established players like Nvidia.

Baseten is a machine learning infrastructure that provides a unified platform for data scientists and engineers to build, train, and deploy machine learning models. It offers a range of features to simplify the ML lifecycle, including data preparation, model training, and deployment. Baseten also provides a marketplace of pre-built models and components that can be used to accelerate the development of ML applications.

Domino Data Lab is an enterprise AI platform that enables users to build, deploy, and manage AI models across any environment. It fosters collaboration, establishes best practices, and ensures governance while reducing costs. The platform provides access to a broad ecosystem of open source and commercial tools, and infrastructure, allowing users to accelerate and scale AI impact. Domino serves as a central hub for AI operations and knowledge, offering integrated workflows, automation, and hybrid multicloud capabilities. It helps users optimize compute utilization, enforce compliance, and centralize knowledge across teams.

Arcee AI is a platform that offers a cost-effective, secure, end-to-end solution for building and deploying Small Language Models (SLMs). It allows users to merge and train custom language models by leveraging open source models and their own data. The platform is known for its Model Merging technique, which combines the power of pre-trained Large Language Models (LLMs) with user-specific data to create high-performing models across various industries.

FuriosaAI is an AI application that offers Hardware RNGD for LLM and Multimodality, as well as WARBOY for Computer Vision. It provides a comprehensive developer experience through the Furiosa SDK, Model Zoo, and Dev Support. The application focuses on efficient AI inference, high-performance LLM and multimodal deployment capabilities, and sustainable mass adoption of AI. FuriosaAI features the Tensor Contraction Processor architecture, software for streamlined LLM deployment, and a robust ecosystem support. It aims to deliver powerful and efficient deep learning acceleration while ensuring future-proof programmability and efficiency.

Striveworks is an AI application that offers a Machine Learning Operations Platform designed to help organizations build, deploy, maintain, monitor, and audit machine learning models efficiently. It provides features such as rapid model deployment, data and model auditability, low-code interface, flexible deployment options, and operationalizing AI data science with real returns. Striveworks aims to accelerate the ML lifecycle, save time and money in model creation, and enable non-experts to leverage AI for data-driven decisions.

Wallaroo.AI is an AI inference platform that offers production-grade AI inference microservices optimized on OpenVINO for cloud and Edge AI application deployments on CPUs and GPUs. It provides hassle-free AI inferencing for any model, any hardware, anywhere, with ultrafast turnkey inference microservices. The platform enables users to deploy, manage, observe, and scale AI models effortlessly, reducing deployment costs and time-to-value significantly.

Qualcomm AI Hub is a platform that allows users to run AI models on Snapdragon® 8 Elite devices. It provides a collaborative ecosystem for model makers, cloud providers, runtime, and SDK partners to deploy on-device AI solutions quickly and efficiently. Users can bring their own models, optimize for deployment, and access a variety of AI services and resources. The platform caters to various industries such as mobile, automotive, and IoT, offering a range of models and services for edge computing.

ClearML is an open-source, end-to-end platform for continuous machine learning (ML). It provides a unified platform for data management, experiment tracking, model training, deployment, and monitoring. ClearML is designed to make it easy for teams to collaborate on ML projects and to ensure that models are deployed and maintained in a reliable and scalable way.

JFrog ML is an AI platform designed to streamline AI development from prototype to production. It offers a unified MLOps platform to build, train, deploy, and manage AI workflows at scale. With features like Feature Store, LLMOps, and model monitoring, JFrog ML empowers AI teams to collaborate efficiently and optimize AI & ML models in production.

Comet ML is a machine learning platform that integrates with your existing infrastructure and tools so you can manage, visualize, and optimize models—from training runs to production monitoring.

ConsoleX is an advanced AI tool that offers a wide range of functionalities to unlock infinite possibilities in the field of artificial intelligence. It provides users with a powerful platform to develop, test, and deploy AI models with ease. With cutting-edge features and intuitive interface, ConsoleX is designed to cater to the needs of both beginners and experts in the AI domain. Whether you are a data scientist, researcher, or developer, ConsoleX empowers you to explore the full potential of AI technology and drive innovation in your projects.

Fortuna is a library for uncertainty quantification that enables users to estimate predictive uncertainty, assess model reliability, trigger human intervention, and deploy models safely. It provides calibration and conformal methods for pre-trained models in any framework, supports Bayesian inference methods for deep learning models written in Flax, and is designed to be intuitive and highly configurable. Users can run benchmarks and bring uncertainty to production systems with ease.

uTensor is an extremely light-weight machine learning inference framework built on Tensorflow and optimized for Arm targets. It consists of a runtime library and an offline tool that handles most of the model translation work. The core runtime is only ~2KB. The workflow involves constructing and training a model in Tensorflow, then using uTensor to produce C++ code for inferencing. The runtime ensures system safety, guarantees RAM usage, and focuses on clear, concise, and debuggable code. The high-level API simplifies tensor handling and operator execution for embedded systems.

The LLM Twin Course is a free, end-to-end framework for building production-ready LLM systems. It teaches you how to design, train, and deploy a production-ready LLM twin of yourself powered by LLMs, vector DBs, and LLMOps good practices. The course is split into 11 hands-on written lessons and the open-source code you can access on GitHub. You can read everything and try out the code at your own pace.

Okay, here is a JSON object with the requested information about the awesome-cuda-tensorrt-fpga repository:

ChatLLM Web is a browser-based AI chat tool powered by WebGPU, providing a seamless and private chat experience. It runs models in a web worker, supports model caching, and offers multi-conversation chat with data stored locally. The tool features a well-designed UI with dark mode, PWA support for offline use, and markdown and streaming response capabilities. Users can deploy it easily on Vercel and interact with the AI like Vicuna in their browser.

LLMWare is a framework for quickly developing LLM-based applications including Retrieval Augmented Generation (RAG) and Multi-Step Orchestration of Agent Workflows. This project provides a comprehensive set of tools that anyone can use - from a beginner to the most sophisticated AI developer - to rapidly build industrial-grade, knowledge-based enterprise LLM applications. Our specific focus is on making it easy to integrate open source small specialized models and connecting enterprise knowledge safely and securely.

Yet Another Chatbot is a sophisticated multimodal chat interface powered by advanced AI models and equipped with a variety of tools. This chatbot can search and browse the web in real-time, query Wikipedia for information, perform news and map searches, execute Python code, compose long-form articles mixing text and images, generate, search, and compare images, analyze documents and images, search and download arXiv papers, save conversations as text and audio files, manage checklists, and track personal improvements. It offers tools for web interaction, Wikipedia search, Python scripting, content management, image handling, arXiv integration, conversation generation, file management, personal improvement, and checklist management.

Atidraw is a web application that allows users to create, enhance, and share drawings using Cloudflare R2 and Cloudflare AI. It features intuitive drawing with signature_pad, AI-powered enhancements such as alt text generation and image generation with Stable Diffusion, global storage on Cloudflare R2, flexible authentication options, and high-performance server-side rendering on Cloudflare Pages. Users can deploy Atidraw with zero configuration on their Cloudflare account using NuxtHub.

Docq is a private and secure GenAI tool designed to extract knowledge from business documents, enabling users to find answers independently. It allows data to stay within organizational boundaries, supports self-hosting with various cloud vendors, and offers multi-model and multi-modal capabilities. Docq is extensible, open-source (AGPLv3), and provides commercial licensing options. The tool aims to be a turnkey solution for organizations to adopt AI innovation safely, with plans for future features like more data ingestion options and model fine-tuning.

PartCAD is a tool for documenting manufacturable physical products, providing tools to maintain product information and streamline workflows at all product lifecycle phases. It is a next-generation CAD tool that focuses on specifying manufacturable physical products using computer-aided design in a more generic sense, including the use of AI models. PartCAD offers modular and reusable packages for product information, generating outputs like product documentation, bill of materials, sourcing information, and manufacturing process specifications. It integrates with third-party tools for iterative improvements, design validation, and manufacturing processes verification. PartCAD also offers supplementary products like a CRM and inventory tool for managing part manufacturing and assembly shops. By enabling easy switching between third-party tools, PartCAD creates a competitive environment for service providers and ensures data sovereignty for users.

Awesome Agents is a curated list of open source AI agents designed for various tasks such as private interactions with documents, chat implementations, autonomous research, human-behavior simulation, code generation, HR queries, domain-specific research, and more. The agents leverage Large Language Models (LLMs) and other generative AI technologies to provide solutions for complex tasks and projects. The repository includes a diverse range of agents for different use cases, from conversational chatbots to AI coding engines, and from autonomous HR assistants to vision task solvers.

The LLM Engineer's Handbook is an official repository containing a comprehensive guide on creating an end-to-end LLM-based system using best practices. It covers data collection & generation, LLM training pipeline, a simple RAG system, production-ready AWS deployment, comprehensive monitoring, and testing and evaluation framework. The repository includes detailed instructions on setting up local and cloud dependencies, project structure, installation steps, infrastructure setup, pipelines for data processing, training, and inference, as well as QA, tests, and running the project end-to-end.

MPLSandbox is an out-of-the-box multi-programming language sandbox designed to provide unified and comprehensive feedback from compiler and analysis tools for LLMs. It simplifies code analysis for researchers and can be seamlessly integrated into LLM training and application processes to enhance performance in a range of code-related tasks. The sandbox environment ensures safe code execution, the code analysis module offers comprehensive analysis reports, and the information integration module combines compilation feedback and analysis results for complex code-related tasks.

大型语言模型的学习和训练指导专家

Formador para la certificación de ML Engineer en GCP, con respuestas y explicaciones detalladas.

Your expert in libtorch and C++ programming.

Expert in Hugging Face platform tools and resources

A witty yet succinct guide for HuggingFace, offering technical assistance on using the platform - based on their Learning Hub

I'm an expert in TensorFlow, providing detailed, accurate guidance for all skill levels.

NeurIPS 2023 Gateway

I'm a Python and PyTorch expert with knowledge of ML infrastructure requirements ready to help you build and scale your ML projects.

Adapts explanations to user's TensorFlow skill level

Expert in PyTorch, adept at simplifying complex concepts.

I'm your Machine Learning and Python mentor, ready to teach and guide you.

An expert MLOps engineer assisting in DevOps and pipeline optimization.

Evolves with user interactions in data science.

Your AI research aide for the latest in ML.

资深AI研究者，专长于论文解读、技术解析及代码编写。

Compresses & decompresses sparse priming data.

Up-to-date FastAPI coding assistant with knowledge of the latest version. Part of the [latest] GPTs family.

A data assistant for devs, now with real video and image links.

A creative aide for designing new GPT models, skilled in ideation and prompting.

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