Results for train_hard

Complete machine learning framework in Rust - tensors, neural networks, 85+ ML algorithms, GPU acceleration, WASM, FFI, model serving, compiler optimizations, distributed training, and 8 hardware accelerators - all included by default

Neural network layers for GhostFlow ML framework

Senior SysAdmin, Network Admin, Data Analyst, and Software Engineer living in your terminal. A high-precision local AI agent harness for LM Studio, Ollama, and other local OpenAI-compatible runtimes that runs 100% on your own silicon. Reads repos, edits files, runs builds, inspects full network state and workstation telemetry, and runs real Python/JS for data analysis.

Geometric region embeddings (boxes, cones, octagons, Gaussians, hyperbolic intervals, sheaf networks) for subsumption, entailment, and logical query answering

The autonomous, self-improving AI agent. Single Rust binary. Every channel. Install with: cargo install opencrabs

A composable, deterministic text data pipeline for ML. Ingest, denoise, chunk, split, and sample multi-source corpora into reproducible training triplets.

Logic-as-Tensor planning layer - meta crate re-exporting all TensorLogic components

Compiler for transforming logic expressions into tensor computation graphs

An adaptive machine-learning-based cache tracker/replacement policy. From ticki's tfs/mlcr.

Predictive Coding Actor-Critic reinforcement learning framework — pure Rust, zero ML dependencies

Training loops, loss composition, and optimization schedules for TensorLogic

Core types, traits, and error surfaces shared across XLOG