Search Results for "model-builder" - Page 2

...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.

...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.

LiteBox is a security-focused “library OS” sandboxing project that aims to shrink the interface between an application and its host environment to reduce attack surface. Instead of relying solely on broad OS-level permissions, it focuses on isolating workloads by tightly controlling the boundary where code interacts with host services and system resources. The design emphasizes interoperability across different integration layers, describing a separation between “North” shims (how apps or...

Bend is an interactive programming environment (REPL) built on top of the Kotlin language, designed to allow users to explore, experiment, and learn Kotlin in a live, feedback-driven manner. The tool lets you define variables, functions, or values at the prompt and iteratively refine them—immediately seeing output and types—while preserving state across commands. It emphasizes discoverability and experimentation: users can inspect functions, call them on sample inputs, and evolve logic...

...You provide some functions that are executed for new video frames and Pipeless takes care of everything else. You can easily use industry-standard models, such as YOLO, or load your custom model in one of the supported inference runtimes. Pipeless ships some of the most popular inference runtimes, such as the ONNX Runtime, allowing you to run inference with high performance on CPU or GPU out-of-the-box. You can deploy your Pipeless application with a single command to edge and IoT devices or the cloud.

...Anonymize sensitive production data. Create realistic data to your specifications. Synth uses a declarative configuration language that allows you to specify your entire data model as code. Synth can import data straight from existing sources and automatically create accurate and versatile data models. Synth supports semi-structured data and is database agnostic, playing nicely with SQL and NoSQL databases. Synth supports generation for thousands of semantic types such as credit card numbers, email addresses, and more.