Best AI tools for< Deploy Custom Model >

FriendliAI is a generative AI infrastructure company that offers efficient, fast, and reliable generative AI inference solutions for production. Their cutting-edge technologies enable groundbreaking performance improvements, cost savings, and lower latency. FriendliAI provides a platform for building and serving compound AI systems, deploying custom models effortlessly, and monitoring and debugging model performance. The application guarantees consistent results regardless of the model used and offers seamless data integration for real-time knowledge enhancement. With a focus on security, scalability, and performance optimization, FriendliAI empowers businesses to scale with ease.

Replicate is an AI tool that allows users to run and fine-tune open-source models, deploy custom models at scale, and generate images, text, videos, music, and speech with just one line of code. It provides a platform for the community to contribute and explore thousands of production-ready AI models, enabling users to push the boundaries of AI beyond academic papers and demos. With features like fine-tuning models, deploying custom models, and scaling on Replicate, users can easily create and deploy AI solutions for various tasks.

Replicate is an AI tool that allows users to run and fine-tune open-source models, deploy custom models at scale, and generate various types of content such as images, text, music, and speech with just one line of code. It provides a platform where users can explore and utilize thousands of production-ready AI models contributed by the community. Replicate aims to make AI accessible and practical by enabling users to push AI beyond academic papers and demos.

Cogniflow is a no-code AI platform that allows users to build and deploy custom AI models without any coding experience. The platform provides a variety of pre-built AI models that can be used for a variety of tasks, including customer service, HR, operations, and more. Cogniflow also offers a variety of integrations with other applications, making it easy to connect your AI models to your existing workflow.

Cradl AI is a no-code AI-powered document workflow automation tool that helps organizations automate document-related tasks, such as data extraction, processing, and validation. It uses AI to automatically extract data from complex document layouts, regardless of layout or language. Cradl AI also integrates with other no-code tools, making it easy to build and deploy custom AI models.

Averroes is the #1 AI Automated Visual Inspection Software designed for various industries such as Oil and Gas, Food and Beverage, Pharma, Semiconductor, and Electronics. It offers an end-to-end AI visual inspection platform that allows users to effortlessly train and deploy custom AI models for defect classification, object detection, and segmentation. Averroes provides advanced solutions for quality assurance, including automated defect classification, submicron defect detection, defect segmentation, defect review, and defect monitoring. The platform ensures labeling consistency, offers flexible deployment options, and has shown remarkable improvements in defect detection and productivity for semiconductor OEMs.

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.

Strong Analytics is a data science consulting and machine learning engineering company that specializes in building bespoke data science, machine learning, and artificial intelligence solutions for various industries. They offer end-to-end services to design, engineer, and deploy custom AI products and solutions, leveraging a team of full-stack data scientists and engineers with cross-industry experience. Strong Analytics is known for its expertise in accelerating innovation, deploying state-of-the-art techniques, and empowering enterprises to unlock the transformative value of AI.

Tune AI is an enterprise Gen AI stack that offers custom models to build competitive advantage. It provides a range of features such as accelerating coding, content creation, indexing patent documents, data audit, automatic speech recognition, and more. The application leverages generative AI to help users solve real-world problems and create custom models on top of industry-leading open source models. With enterprise-grade security and flexible infrastructure, Tune AI caters to developers and enterprises looking to harness the power of AI.

Unsloth is an AI tool designed to make finetuning large language models like Llama-3, Mistral, Phi-3, and Gemma 2x faster, use 70% less memory, and with no degradation in accuracy. The tool provides documentation to help users navigate through training their custom models, covering essentials such as installing and updating Unsloth, creating datasets, running, and deploying models. Users can also integrate third-party tools and utilize platforms like Google Colab.

Allganize Inc. is a leading provider of enterprise AI solutions. Their platform enables businesses to build and deploy custom AI applications without the need for coding. Allganize's solutions are used by a variety of industries, including financial services, healthcare, and manufacturing.

PredictModel is an AI tool that specializes in creating custom Machine Learning models tailored to meet unique requirements. The platform offers a comprehensive three-step process, including generating synthetic data, training ML models, and deploying them to AWS. PredictModel helps businesses streamline processes, improve customer segmentation, enhance client interaction, and boost overall business performance. The tool maximizes accuracy through customized synthetic data generation and saves time and money by providing expert ML engineers. With a focus on automated lead prioritization, fraud detection, cost optimization, and planning, PredictModel aims to stay ahead of the curve in the ML industry.

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.

Mirage is a custom AI platform that builds custom LLMs to accelerate productivity. It is backed by Sequoia and offers a variety of features, including the ability to create custom AI models, train models on your own data, and deploy models to the cloud or on-premises.

Chatbase is an AI tool that provides custom ChatGPT models tailored to your data. It allows users to create conversational AI models that are specific to their needs, enabling more engaging and personalized interactions with customers. With Chatbase, users can easily train, deploy, and manage chatbots for various applications such as customer support, virtual assistants, and more. The platform offers advanced natural language processing capabilities to understand and respond to user queries effectively.

Vocode is an open-source voice AI platform that enables users to build, deploy, and scale hyperrealistic voice agents. It offers fully programmable voice bots that can be integrated into workflows without the need for human intervention. With multilingual capability, custom language models, and the ability to connect to knowledge bases, Vocode provides a comprehensive solution for automating actions like scheduling, payments, and more. The platform also offers analytics and monitoring features to track bot performance and customer interactions, making it a valuable tool for businesses looking to enhance customer support and engagement.

OpenAI Platform is a suite of powerful AI tools that can help you build and deploy AI applications. With OpenAI Platform, you can access state-of-the-art AI models, including GPT-3, Codex, and DALL-E 2. You can also use OpenAI Platform to train your own custom AI models. OpenAI Platform is used by businesses of all sizes to build a wide range of AI applications, including chatbots, language translation tools, and image generators.

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.

Contentable.ai is a platform for comparing multiple AI models, rapidly moving from prototyping to production, and management of your custom AI solutions across multiple vendors. It allows users to test multiple AI models in seconds, compare models side-by-side across top AI providers, collaborate on AI models with their team seamlessly, design complex AI workflows without coding, and pay as they go.

re:tune is a no-code AI app solution that provides everything you need to transform your business with AI, from custom chatbots to autonomous agents. With re:tune, you can build chatbots for any use case, connect any data source, and integrate with all your favorite tools and platforms. re:tune is the missing platform to build your AI apps.

FastServe-AI is a machine learning serving tool focused on GenAI & LLMs with simplicity as the top priority. It allows users to easily serve custom models by implementing the 'handle' method for 'FastServe'. The tool provides a FastAPI server for custom models and can be deployed using Lightning AI Studio. Users can install FastServe-AI via pip and run it to serve their own GPT-like LLM models in minutes.

Thinc is a lightweight deep learning library that offers an elegant, type-checked, functional-programming API for composing models, with support for layers defined in other frameworks such as PyTorch, TensorFlow and MXNet. You can use Thinc as an interface layer, a standalone toolkit or a flexible way to develop new models.

WebLLM is a modular and customizable javascript package that directly brings language model chats directly onto web browsers with hardware acceleration. Everything runs inside the browser with no server support and is accelerated with WebGPU. WebLLM is fully compatible with OpenAI API. That is, you can use the same OpenAI API on any open source models locally, with functionalities including json-mode, function-calling, streaming, etc. We can bring a lot of fun opportunities to build AI assistants for everyone and enable privacy while enjoying GPU acceleration.

The Google Cloud Vertex AI sample repository contains notebooks and community content that demonstrate how to develop and manage ML workflows using Google Cloud Vertex AI.

BentoVLLM is an example project demonstrating how to serve and deploy open-source Large Language Models using vLLM, a high-throughput and memory-efficient inference engine. It provides a basis for advanced code customization, such as custom models, inference logic, or vLLM options. The project allows for simple LLM hosting with OpenAI compatible endpoints without the need to write any code. Users can interact with the server using Swagger UI or other methods, and the service can be deployed to BentoCloud for better management and scalability. Additionally, the repository includes integration examples for different LLM models and tools.

The STM32 AI model zoo is a collection of reference machine learning models optimized to run on STM32 microcontrollers. It provides a large collection of application-oriented models ready for re-training, scripts for easy retraining from user datasets, pre-trained models on reference datasets, and application code examples generated from user AI models. The project offers training scripts for transfer learning or training custom models from scratch. It includes performances on reference STM32 MCU and MPU for float and quantized models. The project is organized by application, providing step-by-step guides for training and deploying models.

The Vertex AI SDK for Python is a library that provides a convenient way to use the Vertex AI API. It offers a high-level interface for creating and managing Vertex AI resources, such as datasets, models, and endpoints. The SDK also provides support for training and deploying custom models, as well as using AutoML models. With the Vertex AI SDK for Python, you can quickly and easily build and deploy machine learning models on Vertex AI.

Log10 is a one-line Python integration to manage your LLM data. It helps you log both closed and open-source LLM calls, compare and identify the best models and prompts, store feedback for fine-tuning, collect performance metrics such as latency and usage, and perform analytics and monitor compliance for LLM powered applications. Log10 offers various integration methods, including a python LLM library wrapper, the Log10 LLM abstraction, and callbacks, to facilitate its use in both existing production environments and new projects. Pick the one that works best for you. Log10 also provides a copilot that can help you with suggestions on how to optimize your prompt, and a feedback feature that allows you to add feedback to your completions. Additionally, Log10 provides prompt provenance, session tracking and call stack functionality to help debug prompt chains. With Log10, you can use your data and feedback from users to fine-tune custom models with RLHF, and build and deploy more reliable, accurate and efficient self-hosted models. Log10 also supports collaboration, allowing you to create flexible groups to share and collaborate over all of the above features.

ClearML Serving is a command line utility for model deployment and orchestration, enabling model deployment including serving and preprocessing code to a Kubernetes cluster or custom container based solution. It supports machine learning models like Scikit Learn, XGBoost, LightGBM, and deep learning models like TensorFlow, PyTorch, ONNX. It provides a customizable RestAPI for serving, online model deployment, scalable solutions, multi-model per container, automatic deployment, canary A/B deployment, model monitoring, usage metric reporting, metric dashboard, and model performance metrics. ClearML Serving is modular, scalable, flexible, customizable, and open source.

Xorbits Inference (Xinference) is a powerful and versatile library designed to serve language, speech recognition, and multimodal models. With Xorbits Inference, you can effortlessly deploy and serve your or state-of-the-art built-in models using just a single command. Whether you are a researcher, developer, or data scientist, Xorbits Inference empowers you to unleash the full potential of cutting-edge AI models.

OpenLLM is a platform that helps developers run any open-source Large Language Models (LLMs) as OpenAI-compatible API endpoints, locally and in the cloud. It supports a wide range of LLMs, provides state-of-the-art serving and inference performance, and simplifies cloud deployment via BentoML. Users can fine-tune, serve, deploy, and monitor any LLMs with ease using OpenLLM. The platform also supports various quantization techniques, serving fine-tuning layers, and multiple runtime implementations. OpenLLM seamlessly integrates with other tools like OpenAI Compatible Endpoints, LlamaIndex, LangChain, and Transformers Agents. It offers deployment options through Docker containers, BentoCloud, and provides a community for collaboration and contributions.

The WhatsApp AI Bot is a chatbot that utilizes various AI models APIs to generate responses to user input. Users can interact with the bot using commands to access different AI models such as Gemini, Gemini-Vision, CHAT-GPT, DALL-E, and Stability AI. Additionally, users have the flexibility to create their own custom models to personalize the bot's behavior. The bot operates on WhatsApp Web through Puppeteer and requires API keys for Gemini, OpenAI, and StabilityAI. It provides a range of functionalities and customization options for users interested in AI-powered chatbots.

Farfalle is an open-source AI-powered search engine that allows users to run their own local LLM or utilize the cloud. It provides a tech stack including Next.js for frontend, FastAPI for backend, Tavily for search API, Logfire for logging, and Redis for rate limiting. Users can get started by setting up prerequisites like Docker and Ollama, and obtaining API keys for Tavily, OpenAI, and Groq. The tool supports models like llama3, mistral, and gemma. Users can clone the repository, set environment variables, run containers using Docker Compose, and deploy the backend and frontend using services like Render and Vercel.

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).

Talk With Gemini is a web application that allows users to deploy their private Gemini application for free with one click. It supports Gemini Pro and Gemini Pro Vision models. The application features talk mode for direct communication with Gemini, visual recognition for understanding picture content, full Markdown support, automatic compression of chat records, privacy and security with local data storage, well-designed UI with responsive design, fast loading speed, and multi-language support. The tool is designed to be user-friendly and versatile for various deployment options and language preferences.

Zeta is a tool designed to build state-of-the-art AI models faster by providing modular, high-performance, and scalable building blocks. It addresses the common issues faced while working with neural nets, such as chaotic codebases, lack of modularity, and low performance modules. Zeta emphasizes usability, modularity, and performance, and is currently used in hundreds of models across various GitHub repositories. It enables users to prototype, train, optimize, and deploy the latest SOTA neural nets into production. The tool offers various modules like FlashAttention, SwiGLUStacked, RelativePositionBias, FeedForward, BitLinear, PalmE, Unet, VisionEmbeddings, niva, FusedDenseGELUDense, FusedDropoutLayerNorm, MambaBlock, Film, hyper_optimize, DPO, and ZetaCloud for different tasks in AI model development.

ddddocr is a Rust version of a simple OCR API server that provides easy deployment for captcha recognition without relying on the OpenCV library. It offers a user-friendly general-purpose captcha recognition Rust library. The tool supports recognizing various types of captchas, including single-line text, transparent black PNG images, target detection, and slider matching algorithms. Users can also import custom OCR training models and utilize the OCR API server for flexible OCR result control and range limitation. The tool is cross-platform and can be easily deployed.

The Looker GenAI Extension provides code examples and resources for building a Looker Extension that integrates with Vertex AI Large Language Models (LLMs). Users can leverage the power of LLMs to enhance data exploration and analysis within Looker. The extension offers generative explore functionality to ask natural language questions about data and generative insights on dashboards to analyze data by asking questions. It leverages components like BQML Remote Models, BQML Remote UDF with Vertex AI, and Custom Fine Tune Model for different integration options. Deployment involves setting up infrastructure with Terraform and deploying the Looker Extension by creating a Looker project, copying extension files, configuring BigQuery connection, connecting to Git, and testing the extension. Users can save example prompts and configure user settings for the extension. Development of the Looker Extension environment includes installing dependencies, starting the development server, and building for production.

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