Search Results for "model-builder" - Page 19
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Showing 2118 open source projects for "model-builder"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
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zero-native
Build desktop + mobile apps with Zig and web UI
...The project supports lightweight system WebView rendering for smaller binaries, while also offering Chromium through CEF when predictable rendering is more important. Its Zig foundation enables fast native rebuilds and direct access to platform SDKs, native libraries, codecs, and local integrations. The app model includes a manifest for metadata, icons, windows, frontend assets, engine selection, security policy, bridge permissions, and packaging inputs. It is still pre-release, but it provides a promising path for developers who want web UI productivity with a leaner native runtime than heavier desktop frameworks. -
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ollama-hpp
Modern, Header-only C++ bindings for the Ollama API
...It includes support for streaming responses, enabling applications to process output as it is generated rather than waiting for full completions. The project also evolves alongside the Ollama API, adding support for newer features such as blob handling and improved model interaction capabilities. Its design prioritizes simplicity, allowing developers to quickly integrate AI features without introducing large dependencies. -
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LLM Tornado
The .NET library to build AI agents with 30+ built-in connectors
...It supports multimodal inputs and outputs, including text, images, audio, and documents, making it suitable for a wide range of AI applications. LLMTornado also integrates advanced protocols such as Model Context Protocol and agent-to-agent communication, enabling complex interactions between systems. With built-in support for local deployments, enterprise guardrails, and observability features. -
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any-llm
Communicate with an LLM provider using a single interface
any-llm is a unified SDK and platform developed by Mozilla AI that allows developers to interact with multiple large language model providers through a single, consistent interface. Instead of rewriting code for each provider, developers can switch between services like OpenAI, Anthropic, Mistral, and Ollama simply by changing configuration parameters. The project is designed to be framework-agnostic, making it easy to integrate into scripts, applications, or production systems without being tied to a specific stack. ... -
$300 Free Credits to Build on Google CloudStart your next project with $300 in free Google Cloud credit. Spin up VMs, run containers, query petabytes in BigQuery, or build agents with Gemini Enterprise Agent Platform. Once your credits are used, keep building with 20+ always-free tier products including Compute Engine, Cloud Storage, GKE, and Cloud Run functions. No commitment required—just sign up and start building.
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Flowbite Svelte
Official Svelte components built for Flowbite and Tailwind CSS
...The library provides a comprehensive collection of interactive elements such as modals, dropdowns, navigation bars, forms, and data display components, all implemented with Svelte’s reactive model rather than external JavaScript logic. Because Svelte compiles components into efficient JavaScript that directly manipulates the DOM, Flowbite Svelte benefits from high performance and minimal runtime overhead while still offering rich interactivity. The project is designed to accelerate frontend development by offering ready-made building blocks that can be easily customized using Tailwind utility classes, making it suitable for both rapid prototyping and production applications. -
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tachyonfx
Effects and animation library for Ratatui applications
...The library focuses on enhancing the visual expressiveness of terminal applications, which are traditionally static, by introducing motion, interpolation, and smooth transitions between UI states. TachyonFX integrates deeply with Ratatui’s rendering model, allowing developers to apply effects to widgets, layouts, or entire scenes without rewriting core UI logic. It also supports real-time updates and interactive behaviors, making it suitable for applications that require responsive visual feedback. -
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wazero
The zero dependency WebAssembly runtime for Go developers
...One of its defining characteristics is its pure Go implementation, which simplifies cross-compilation and deployment across different platforms. Wazero is designed to securely run code compiled from other languages, leveraging WebAssembly’s sandboxing model to isolate execution and reduce risk. It is particularly useful for embedding plugins, extending applications, or running untrusted code in a controlled environment. The runtime also provides flexible configuration options and integrates seamlessly into Go-based systems, making it a powerful tool for modern backend and systems development. -
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lldap
Light LDAP implementation
...Written in Rust, lldap benefits from strong memory safety guarantees and performance efficiency, making it suitable for self-hosted environments and small-to-medium-scale deployments. The project emphasizes usability, offering a more approachable configuration model and integration capabilities for authentication and identity management systems. lldap is particularly useful for developers and organizations that need LDAP-compatible authentication without the complexity of legacy systems like OpenLDAP. Its design prioritizes clarity, maintainability, and ease of deployment, aligning with modern infrastructure practices. -
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GCP Config Connector
GCP Config Connector, a Kubernetes add-on for managing GCP resources
...This makes the project highly valuable for teams practicing GitOps, platform engineering, or Kubernetes-centered operations, because it brings cloud resource management into the same control model used for application deployment. The repository also reflects an active emphasis on resource development and reconciliation reliability, including a newer direct development approach intended to provide a more Kubernetes-native authoring experience. -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Functions Framework for Node.js
FaaS (Function as a service) framework for writing portable Node.js
Functions Framework for Node.js is a lightweight runtime library that allows developers to write and run portable serverless functions locally or in cloud environments using standard Node.js. It provides a consistent execution model that mimics Google Cloud Functions, enabling developers to build, test, and debug functions on their local machine before deploying them to production. The framework supports multiple function signature types, including HTTP-based functions and event-driven functions, and automatically parses incoming request payloads into structured objects that can be easily consumed by application logic. ... -
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X For You Feed Algorithm
Algorithm powering the For You feed on X
...The repository contains the full pipeline that ingests user engagement and content candidate data, processes it through retrieval, hydration, filtering, scoring, and selection layers, and ultimately ranks posts to show what appears in a user’s feed. At its heart, the system uses a transformer-based model adapted from xAI’s Grok architecture to predict probabilities for various user actions (such as likes, replies, reposts, clicks, and negative signals), then combines those into a weighted final score that drives ranking. -
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Substrate
An Open-source Framework for Human Understanding, Meaning, Progress
Substrate is an open-source framework focused on human understanding, meaning, and progress. It aims to surface and structure conceptual objects—ideas, problems, beliefs, models, frames, goals, arguments, sources—to make them more transparent, discussable and actionable. The goal is to enable communities to collectively build and maintain a repository of these objects so that complex systems of meaning and progress can be mapped, analyzed and improved. It is relatively ambitious in... -
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Uncertainty Baselines
High-quality implementations of standard and SOTA methods
Uncertainty Baselines is a collection of strong, well-documented training pipelines that make it straightforward to evaluate predictive uncertainty in modern machine learning models. Rather than offering toy scripts, it provides end-to-end recipes—data input, model architectures, training loops, evaluation metrics, and logging—so results are comparable across runs and research groups. The library spans canonical modalities and tasks, from image classification and NLP to tabular problems, with baselines that cover both deterministic and probabilistic approaches. Techniques include deep ensembles, Monte Carlo dropout, temperature scaling, stochastic variational inference, heteroscedastic heads, and out-of-distribution detection workflows. ... -
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TarpC
An RPC framework for Rust with a focus on ease of use
...The framework is transport-agnostic: it commonly uses Tokio with serde-based codecs, but you can plug in your own framing and serialization. It bakes in RPC concerns such as deadlines, cancellation, and context propagation so production behavior is predictable under load. The programming model feels native—call methods on a client stub and await results—while the server side exposes clean concurrency primitives for handling many requests. Because the interface is just Rust code, refactoring and IDE tooling work naturally without an external IDL. -
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CoreNet
CoreNet: A library for training deep neural networks
CoreNet is Apple’s internal deep learning framework for distributed neural network training, designed for high scalability, low-latency communication, and strong hardware efficiency. It focuses on enabling large-scale model training across clusters of GPUs and accelerators by optimizing data flow and parallelism strategies. CoreNet provides abstractions for data, tensor, and pipeline parallelism, allowing models to scale without code duplication or heavy manual configuration. Its distributed runtime manages synchronization, load balancing, and mixed-precision computation to maximize throughput while minimizing communication bottlenecks. ... -
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JavaScript Obfuscator
A powerful obfuscator for JavaScript and Node.js
...Advanced options include self-defending code, domain locking, debug/console protection, and property key transformation, allowing you to tailor defenses to your threat model. The tool supports source maps and granular “threshold”/whitelist settings so you can balance protection with performance and debuggability. It works with modern JavaScript syntax and integrates into build pipelines to protect selected bundles or modules automatically. Teams use it to deter casual inspection of proprietary logic, license checks, or anti-abuse heuristics shipped to the browser or Node targets. -
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Elixir Companies
A list of companies currently using Elixir in production
...Beyond simple listings, the project highlights the breadth of Elixir usage—from startups to large enterprises—and helps newcomers see real-world adoption. The codebase itself is an example Phoenix application, offering a transparent, collaborative model for community content. Over time, the directory has become a reference point frequently cited when assessing Elixir’s ecosystem health and job market. -
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Superduper
Superduper: Integrate AI models and machine learning workflows
...Developers may leverage Superduper by building compositional and declarative objects that out-source the details of deployment, orchestration versioning, and more to the Superduper engine. This allows developers to completely avoid implementing MLOps, ETL pipelines, model deployment, data migration, and synchronization. Using Superduper is simply "CAPE": Connect to your data, apply arbitrary AI to that data, package and reuse the application on arbitrary data, and execute AI-database queries and predictions on the resulting AI outputs and data. -
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AtomicServer
An open source headless CMS / real-time database
Create, share, fetch, and model Atomic Data! AtomicServer is a lightweight, yet powerful CMS / Graph Database. Atomic Data is a modular specification for sharing, modifying, and modeling graph data. It combines the ease of use of JSON, the connectivity of RDF (linked data), and the reliability of type-safety. Atomic Data uses links to connect pieces of data, and therefore makes it easier to connect datasets to each other - even when these datasets exist on separate machines. -
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zag
Finite state machines for building accessible design systems and UI
A collection of framework-agnostic UI components patterns like an accordion, menu, and dialog that can be used to build design systems for React, Vue, and Solid.js. Simple, resilient component logic. Write component logic once and use it anywhere. Built-in adapters that connect machine output to DOM semantics in a WAI-ARIA-compliant way. Component logic is largely JavaScript code and can be consumed in any JS framework. Zag machine APIs are completely headless and unstyled. Use your favorite... -
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Eloquent Viewable
Associate views with Eloquent models in Laravel
Sometimes you don't want to pull in a third-party service like Google Analytics to track your application's page views. Then this package comes in handy. Eloquent Viewable allows you to easily associate views with Eloquent models. It's designed with simplicity in mind. This package stores each view record individually in the database. The advantage of this is that it allows us to make very specific counts. For example, if we want to know how many people has viewed a specific post between... -
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OptScale
FinOps and MLOps platform to run ML/AI and regular cloud workloads
...OptScale allows ML teams to multiply the number of ML/AI experiments running in parallel while efficiently managing and minimizing costs associated with cloud and infrastructure resources. OptScale MLOps capabilities include ML model leaderboards, performance bottleneck identification and optimization, bulk run of ML/AI experiments, experiment tracking, and more. The solution enables ML/AI engineers to run automated experiments based on datasets and hyperparameter conditions within the defined infrastructure budget. Certified FinOps solution with the best cloud cost optimization engine, providing rightsizing recommendations, Reserved Instances/Savings Plans, and dozens of other optimization scenarios. ... -
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Deckhouse
Kubernetes platform from Flant
...Deckhouse has vanilla Kubernetes under the hood and integrates a balanced set of Open Source tools that have become the industry standard. Out-of-the-box secure configuration of the Kubernetes cluster, least component privileges, pre-configured role model, end-to-end object identity in the audit system, and integration with external directory services. Built-in implementation of Pod Security Standards and a ready-to-use, extensible set of recommended policies. Deckhouse automates many routine deployment, scaling, and infrastructure management operations out of the box. It manages system software on the nodes (kernel, CRI, kubelet), basic Kubernetes components (control plane, etc, certificates, etc.). -
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Stock prediction deep neural learning
Predicting stock prices using a TensorFlow LSTM
Predicting stock prices can be a challenging task as it often does not follow any specific pattern. However, deep neural learning can be used to identify patterns through machine learning. One of the most effective techniques for series forecasting is using LSTM (long short-term memory) networks, which are a type of recurrent neural network (RNN) capable of remembering information over a long period of time. This makes them extremely useful for predicting stock prices. Predicting stock... -
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Mobility
Pluggable Ruby translation framework
...The default way to store translations is to put them all in a set of two shared tables, but many alternatives are also supported, including translatable columns and model translation tables, as well as database-specific storage solutions such as json/jsonb and Hstore (for PostgreSQL).
