Showing 14 open source projects for "programming learning system"

View related business solutions
  • Build Agents and Models on One Platform Icon
    Build Agents and Models on One Platform

    Everything you need to build production-ready agents and models. Access 200+ Google and third-party AI models and tools.

    Gemini 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.
    Start Free
  • $300 Free Credits to Build on Google Cloud Icon
    $300 Free Credits to Build on Google Cloud

    New customers can spin up VMs, build with AI, and query data at no cost.

    Put your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
    Start Free
  • 1
    Tabby

    Tabby

    Self-hosted AI coding assistant

    Tabby is an open-source, self-hosted AI coding assistant that provides code completion and suggestions within your preferred development environment. It enhances developer productivity by leveraging machine learning models to predict and generate code snippets.
    Downloads: 2 This Week
    Last Update:
    See Project
  • 2
    rust-bert

    rust-bert

    Rust native ready-to-use NLP pipelines and transformer-based models

    rust-bert is a Rust-based implementation of transformer-based natural language processing models that provides ready-to-use pipelines for tasks such as text classification, summarization, and question answering. The project ports many capabilities of the Hugging Face Transformers ecosystem into the Rust programming language. It allows developers to run state-of-the-art NLP models like BERT, GPT-2, and DistilBERT directly within Rust applications while maintaining high performance and memory efficiency. The library integrates with Rust machine learning infrastructure using crates such as tch-rs and ONNX Runtime for model execution. It also includes tokenization utilities, model architectures, and task-specific pipelines that simplify the development of NLP applications. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 3
    PostgresML

    PostgresML

    The GPU-powered AI application database

    PostgresML is a complete platform in a PostgreSQL extension. Build simpler, faster, and more scalable models right inside your database. Explore the SDK and test open source models in our hosted database. Combine and automate the entire workflow from embedding generation to indexing and querying for the simplest (and fastest) knowledge-based chatbot implementation. Leverage multiple types of natural language processing and machine learning models such as vector search and personalization...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 4
    Cog

    Cog

    Package and deploy machine learning models using Docker containers

    Cog is an open source tool designed to package machine learning models into standardized, production-ready containers. It simplifies the process of deploying models by automatically generating Docker images based on a simple configuration file, eliminating the need to manually write complex Dockerfiles. Developers can define the runtime environment, dependencies, and Python versions required for their models, allowing Cog to build a consistent container environment that follows best...
    Downloads: 0 This Week
    Last Update:
    See Project
  • Go from Code to Production URL in Seconds Icon
    Go from Code to Production URL in Seconds

    Cloud Run deploys apps in any language instantly. Scales to zero. Pay only when code runs.

    Skip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
    Start Free
  • 5
    ort

    ort

    Fast ML inference & training for ONNX models in Rust

    ort is a high-performance Rust library that provides bindings to ONNX Runtime, enabling developers to run machine learning inference and training workflows directly within Rust applications using the standardized ONNX model format. It is designed to bridge the gap between modern machine learning frameworks and systems programming by offering a safe, ergonomic API for executing models originally built in ecosystems like PyTorch, TensorFlow, or scikit-learn.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 6
    DeepProve

    DeepProve

    Framework to prove inference of ML models blazingly fast

    DeepProve is an advanced cryptographic framework designed to verify machine learning model inference using zero-knowledge proofs, enabling trustless validation of AI computations without exposing underlying data. The project focuses on zkML, a rapidly emerging field that combines machine learning with zero-knowledge cryptography to ensure both privacy and correctness. It supports neural network architectures such as multilayer perceptrons and convolutional neural networks, allowing...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 7
    Lightpanda Browser

    Lightpanda Browser

    Lightpanda: the headless browser designed for AI and automation

    ...This design allows it to execute JavaScript and interact with web pages while avoiding the overhead associated with rendering images, fonts, and layout elements intended for visual display. The browser is implemented using the Zig programming language and integrates the V8 JavaScript engine to run modern web applications and scripts efficiently. Because it avoids graphical rendering and other heavy browser components, the system uses significantly less memory and launches almost instantly compared to conventional browsers such as Chrome.
    Downloads: 16 This Week
    Last Update:
    See Project
  • 8
    Korvus

    Korvus

    Korvus is a search SDK that unifies the entire RAG pipeline

    ...By leveraging PostgresML and vector extensions such as pgvector, Korvus eliminates the need for external microservices typically used for AI search architectures, reducing both system complexity and latency. The architecture enables machine learning operations to occur directly in the database, minimizing data transfer between services and improving overall performance for large datasets.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 9
    MusicGPT

    MusicGPT

    Generate music based on natural language prompts using LLMs

    ...The software allows users to run advanced music generation systems directly on their own devices without requiring heavy dependencies such as Python or full machine learning frameworks. Instead, it provides a lightweight environment capable of executing music generation models locally on CPUs or GPUs while maintaining strong performance across operating systems including Windows, macOS, and Linux. Users can describe a musical style, mood, or instrumentation using text prompts, and the system produces original audio samples based on those instructions. ...
    Downloads: 14 This Week
    Last Update:
    See Project
  • Demo Series - Small Business Backup By Veeam Icon
    Demo Series - Small Business Backup By Veeam

    Learn how to protect your Microsoft 365 data, with simple, actionable tips today.

    Watch this on-demand demo series and learn how to protect your Microsoft 365 data with clear, simple, actionable steps that are easy to implement for businesses of all sizes.
    Watch Demo Series
  • 10
    Floneum

    Floneum

    Instant, controllable, local pre-trained AI models in Rust

    ...Many plugins can be written in different programming languages and compiled to WebAssembly modules, allowing them to run safely within the system. The platform is implemented primarily in Rust and emphasizes performance, modularity, and local execution.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 11
    Rivet

    Rivet

    Visual AI IDE for building agents with prompt chains and graphs

    Rivet is an open source visual AI programming environment designed to help developers build complex AI agents using a node-based interface and prompt chaining workflows. It provides a desktop application that allows users to visually construct and debug AI logic as interconnected graphs, making it easier to manage sophisticated interactions between language models and external tools. Rivet also includes a TypeScript library that enables these visual graphs to be executed and integrated...
    Downloads: 1 This Week
    Last Update:
    See Project
  • 12
    Luminal

    Luminal

    Deep learning at the speed of light

    Luminal is a framework designed to accelerate and simplify the development of systems-level data applications by using a typed, functional, and streaming-first approach. Instead of treating data processing as a series of ad-hoc scripts, Luminal models transformations as strongly typed building blocks that can be composed into reliable, scalable pipelines. The project emphasizes correctness and performance by requiring explicit types for the data flowing through transformations, reducing...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 13
    SIG Rust

    SIG Rust

    Rust language bindings for TensorFlow

    SIG Rust provides idiomatic Rust bindings for TensorFlow, making it possible for developers to work with TensorFlow functionality from within the Rust programming language. Rather than replacing TensorFlow itself, it acts as an integration layer that connects Rust applications to the TensorFlow C API. The repository is designed for developers who want Rust’s performance, safety, and systems programming strengths while still accessing TensorFlow’s machine learning capabilities. It includes setup instructions that explain how the crate can automatically download or compile the required TensorFlow shared libraries, which lowers the barrier to getting started. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 14
    Weld

    Weld

    High-performance runtime for data analytics applications

    Weld is a programming language and runtime designed to improve the performance of data-intensive applications by optimizing computations across multiple libraries. Instead of optimizing individual functions independently, Weld introduces an intermediate representation that allows different frameworks to share optimization opportunities. This approach reduces data movement between libraries and enables the system to generate highly optimized machine code for parallel execution. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next