Best AI Development Platforms for Hugging Face

Union.ai Benefits: - Accelerated Data Processing & ML: Union.ai significantly speeds up data processing and machine learning. - Built on Trusted Open-Source: Leverages the robust open-source project Flyte™, ensuring a reliable and tested foundation for your ML projects. - Kubernetes Efficiency: Harnesses the power and efficiency of Kubernetes along with enhanced observability and enterprise features. - Optimized Infrastructure: Facilitates easier collaboration among Data and ML teams on optimized infrastructures, boosting project velocity. - Breaks Down Silos: Tackles the challenges of distributed tooling and infrastructure by simplifying work-sharing across teams and environments with reusable tasks, versioned workflows, and an extensible plugin system. - Seamless Multi-Cloud Operations: Navigate the complexities of on-prem, hybrid, or multi-cloud setups with ease, ensuring consistent data handling, secure networking, and smooth service integrations. - Cost Optimization: Keeps a tight rein on your compute costs, tracks usage, and optimizes resource allocation even across distributed providers and instances, ensuring cost-effectiveness.

The AI Knowledge Platform. The Pinecone Database, Inference, and Assistant make building high-performance vector search apps easy. Fully managed and developer-friendly, the database is easily scalable without any infrastructure problems. Once you have vector embeddings created, you can search and manage them in Pinecone to power semantic searches, recommenders, or other applications that rely upon relevant information retrieval. Even with billions of items, ultra-low query latency Provide a great user experience. You can add, edit, and delete data via live index updates. Your data is available immediately. For more relevant and quicker results, combine vector search with metadata filters. Our API makes it easy to launch, use, scale, and scale your vector searching service without worrying about infrastructure. It will run smoothly and securely.

AI agents that interact and answer questions with users and complete tasks using your data and APIs. AI that can answer questions, summarize and extract insights from any long document. Transfer styles and formats, as well as tags and summaries between documents and data sources. Stack AI is used by developer teams to automate customer service, process documents, qualify leads, and search libraries of data. With a single button, you can try multiple LLM architectures and prompts. Collect data, run fine-tuning tasks and build the optimal LLM to fit your product. We host your workflows in APIs, so that your users have access to AI instantly. Compare the fine-tuning services of different LLM providers.

Flowise is open source and will always be free to use for commercial and private purposes. Build LLMs apps easily with Flowise, an open source UI visual tool to build your customized LLM flow using LangchainJS, written in Node Typescript/Javascript. Open source MIT License, see your LLM applications running live, and manage component integrations. GitHub Q&A using conversational retrieval QA chains. Language translation using LLM chains with a chat model and chat prompt template. Conversational agent for chat model that uses chat-specific prompts.

Create generative AI apps for engineers and not just ML practitioners. Focus on creating instead of configuring. No more switching platforms or wrestling with APIs. Use a familiar interface for AI and to prompt engineers. Workbooks can be easily streamlined into templates by using parameters. Create workflows using model outputs from LLMs and image and audio models. Create groups to manage workbooks between your teammates. Share your workbook with your team or the public, or to specific organizations that you define. Workbooks can be commented on and compared with your team. Create templates for you, your team or the developer community. Get started quickly by using templates to see what others are building.

PostgresML is an entire platform that comes as a PostgreSQL Extension. Build simpler, faster and more scalable model right inside your database. Explore the SDK, and test open-source models in our hosted databases. Automate the entire workflow, from embedding creation to indexing and Querying for the easiest (and fastest) knowledge based chatbot implementation. Use multiple types of machine learning and natural language processing models, such as vector search or personalization with embeddings, to improve search results. Time series forecasting can help you gain key business insights. SQL and dozens regression algorithms allow you to build statistical and predictive models. ML at database layer can detect fraud and return results faster. PostgresML abstracts data management overheads from the ML/AI cycle by allowing users to run ML/LLM on a Postgres Database.

Choose the appropriate app type. Choose the output and input required for the app. Add data from existing sources such as files, URLs, sitemaps and YouTube links. You can also add data from Notion exports, Google Drive and other sources. Attach these data sources in the app builder. Save and publish your application. You can embed the code in your website or access it directly from the dedicated app page. Our APIs allow you to run the app directly from your application. Promptly offers embeddable widgets you can easily integrate in your website. These widgets can be used to create conversational AI applications, or to add a bot to your website. Customize the look and feel of the chatbot to match your website. Include a logo.

Lilac is a free open-source tool that allows data and AI practitioners improve their products through better data. Understanding your data is easy with powerful filtering and search. Work together with your team to create a single dataset. Use best practices for data curation to reduce the size of your dataset and training costs and time. Our diff viewer allows you to see how your pipeline affects your data. Clustering is an automatic technique that assigns categories to documents by analyzing their text content. Similar documents are then placed in the same category. This reveals your dataset's overall structure. Lilac uses LLMs and state-of-the art algorithms to cluster the data and assign descriptive, informative titles. We can use keyword search before we do advanced searches, such as concept or semantic searching.

Our open-source research efforts are focused on both the new "ware" (middleware and "software" which will wrap and integrate LLMs) as well as building high quality, automation-focused enterprise model available in Hugging Face. LLMWare is also a coherent, high quality, integrated and organized framework for developing LLM-applications in an open system. This provides the foundation for creating LLM-applications that are designed for AI Agent workflows and Retrieval Augmented Generation. Our LLM framework was built from the ground-up to handle complex enterprise use cases. We can provide pre-built LLMs tailored to your industry, or we can fine-tune and customize an LLM for specific domains and use cases. We provide an end-toend solution, from a robust AI framework to specialized models.

Maxim is a enterprise-grade stack that enables AI teams to build applications with speed, reliability, and quality. Bring the best practices from traditional software development to your non-deterministic AI work flows. Playground for your rapid engineering needs. Iterate quickly and systematically with your team. Organise and version prompts away from the codebase. Test, iterate and deploy prompts with no code changes. Connect to your data, RAG Pipelines, and prompt tools. Chain prompts, other components and workflows together to create and test workflows. Unified framework for machine- and human-evaluation. Quantify improvements and regressions to deploy with confidence. Visualize the evaluation of large test suites and multiple versions. Simplify and scale human assessment pipelines. Integrate seamlessly into your CI/CD workflows. Monitor AI system usage in real-time and optimize it with speed.

Lunary is a platform for AI developers that helps AI teams to manage, improve and protect chatbots based on Large Language Models (LLM). It includes features like conversation and feedback tracking as well as analytics on costs and performance. There are also debugging tools and a prompt directory to facilitate team collaboration and versioning. Lunary integrates with various LLMs, frameworks, and languages, including OpenAI, LangChain and JavaScript, and offers SDKs in Python and JavaScript. Guardrails to prevent malicious prompts or sensitive data leaks. Deploy Kubernetes/Docker in your VPC. Your team can judge the responses of your LLMs. Learn what languages your users speak. Experiment with LLM models and prompts. Search and filter everything in milliseconds. Receive notifications when agents do not perform as expected. Lunary's core technology is 100% open source. Start in minutes, whether you want to self-host or use the cloud.

DataChain connects your unstructured cloud files with AI models, APIs and foundational models to enable instant data insights. Its Pythonic stack accelerates the development by tenfold when switching to Python-based data wrangling, without SQL data islands. DataChain provides dataset versioning to ensure full reproducibility and traceability for each dataset. This helps streamline team collaboration while ensuring data integrity. It allows you analyze your data wherever it is stored, storing raw data (S3, GCP or Azure) and metadata in inefficient datawarehouses. DataChain provides tools and integrations which are cloud-agnostic in terms of both storage and computing. DataChain allows you to query your multi-modal unstructured data. You can also apply intelligent AI filters for training data and snapshot your unstructured dataset, the code used for data selection and any stored or computed meta data.

DagsHub, a collaborative platform for data scientists and machine-learning engineers, is designed to streamline and manage their projects. It integrates code and data, experiments and models in a unified environment to facilitate efficient project management and collaboration. The user-friendly interface includes features such as dataset management, experiment tracker, model registry, data and model lineage and model registry. DagsHub integrates seamlessly with popular MLOps software, allowing users the ability to leverage their existing workflows. DagsHub improves machine learning development efficiency, transparency, and reproducibility by providing a central hub for all project elements. DagsHub, a platform for AI/ML developers, allows you to manage and collaborate with your data, models and experiments alongside your code. DagsHub is designed to handle unstructured data, such as text, images, audio files, medical imaging and binary files.

Your team can develop AI applications using models such as GPT-4, and operate them visually. You can deploy your application within 5 minutes, whether it is for internal team use or an external release. Using documents/webpages/Notion content as the context for AI, automatically complete text preprocessing, vectorization and segmentation. No need to learn embedding methods anymore. This will save you weeks of development. Dify offers a smooth user experience for model access and context embedding. It also provides cost control, data annotation, and cost control. You can easily create AI apps for internal team use, or product development. Start with a prompt but go beyond its limitations. Dify offers rich functionality in many scenarios.

Create and manage AI applications without the need to move data to complex vector databases and pipelines. Integrate AI, vector search and real-time inference directly with your database. Python is all you need. All your AI models can be deployed in a single, scalable deployment. The AI models and APIs are automatically updated as new data is processed. You don't need to duplicate your data or create an additional database to use vector searching and build on it. SuperDuperDB allows vector search within your existing database. Integrate and combine models such as those from Sklearn PyTorch HuggingFace, with AI APIs like OpenAI, to build even the most complicated AI applications and workflows. With simple Python commands, deploy all your AI models in one environment to automatically compute outputs in your datastore (inference).

Start building and deploying agents, retrieval-augmented generation and more in the cloud. We charge a flat rate per request. There are two types: document indexation, and generation. Document indexation is adding a document to the knowledge base. Document indexation is the addition a document to your Knowledge Base and generation, that creates LLM writing on your Knowledge Base RAG. Create a RAG workflow using off-the shelf components and prototype the system that best suits your case. We support many auxiliary functions, including reverse-tracing of output into documents and ingestion for a variety of file formats. Agents can be used to enable the LLM's use of tools. Agent-powered systems can decide what data they need and search for it. Our implementation of Agents provides a simple host for execution layers, and pre-built agents for many use scenarios.

Connect AI models to create AI apps in minutes with no code. Your efforts will create the next generation of AI-powered applications. In minutes, you can create AI-powered apps. It's easier than ever to create AI-powered applications. Make money and share your creations around the world. Profit from your unique creations' earning potential. Brancher.ai has over 100 templates that can help you increase your creativity and productivity, from a spark of inspiration to an instant start to a new app.

Cloud-hosted AI packages that are managed and cloud-hosted will make it easier to ship AI faster. GPT-4 support is fully integrated. API tokens do not need to be used. Use our low-code framework to build. All major models can be integrated. Get an instant API by deploying. Scale and share your API without having to manage infrastructure. Make prompts, prompt chains, basic Python, and managed APIs. A clever prompt can be turned into a publicly available API that you can share. Python allows you to add logic and routing smarts. Steamship connects with your favorite models and services, so you don't need to learn a different API for each provider. Steamship maintains model output in a standard format. Consolidate training and inference, vector search, endpoint hosting. Import, transcribe or generate text. It can run all the models that you need. ShipQL allows you to query across all the results. Packages are fully-stack, cloud-hosted AI applications. Each instance you create gives you an API and private data workspace.

With our cloud partners, you can build, train, and deploy your models in cloud using the most recent IPU AI systems and frameworks. This allows you to scale up to large IPU compute seamlessly, while saving on compute costs. Get started with IPUs today by getting on-demand pricing and tiers free of charge from our cloud partners. Our Intelligence Processing Unit (IPU), technology is expected to become the global standard for machine intelligence computing. The Graphcore IPU will have a transformative impact across all industries and sectors. It has the potential to have a real positive societal impact, from drug discovery to disaster recovery to decarbonization. The IPU is an entirely new processor that was specifically designed for AI computation. AI researchers can use the IPU's unique architecture to do completely new types of work that are not possible with current technologies. This will allow them to drive the next generation in machine intelligence.

Create & Share Delightful Apps for Machine Learning. Gradio allows you to quickly and easily demo your machine-learning model. It has a friendly interface that anyone can use, anywhere. Installing Gradio is easy with pip. It only takes a few lines of code to create a Gradio Interface. You can choose between a variety interface types to interface with your function. Gradio is available as a webpage or embedded into Python notebooks. Gradio can generate a link that you can share publicly with colleagues to allow them to interact with your model remotely using their own devices. Once you have created an interface, it can be permanently hosted on Hugging Face. Hugging Face Spaces hosts the interface on their servers and provides you with a shareable link.

With our enterprise Gen AI stack you can go beyond your imagination. You can instantly offload manual tasks and give them to powerful assistants. The sky is the limit. For enterprises that place data security first, fine-tune generative AI models and deploy them on your own cloud securely.

Simplismart’s fastest inference engine allows you to fine-tune and deploy AI model with ease. Integrate with AWS/Azure/GCP, and many other cloud providers, for simple, scalable and cost-effective deployment. Import open-source models from popular online repositories, or deploy your custom model. Simplismart can host your model or you can use your own cloud resources. Simplismart allows you to go beyond AI model deployment. You can train, deploy and observe any ML models and achieve increased inference speed at lower costs. Import any dataset to fine-tune custom or open-source models quickly. Run multiple training experiments efficiently in parallel to speed up your workflow. Deploy any model to our endpoints, or your own VPC/premises and enjoy greater performance at lower cost. Now, streamlined and intuitive deployments are a reality. Monitor GPU utilization, and all of your node clusters on one dashboard. On the move, detect any resource constraints or model inefficiencies.

Unremot is the place to go for anyone who wants to build an AI-based product. With 120+ pre-built AIs, you can launch AI products at 1/3rd of the cost and 2X faster. Even the most complex AI product APIs can be launched and deployed in less than a minute, with minimal or no code. Unremot offers 120+ APIs. Choose the AI API you want to integrate into your product. Unremot will need your API private key in order to authenticate. Unremot's unique URL is the fastest way to connect your product API. The process can take minutes instead of days or weeks.