A large language model (LLM) is a type of machine learning model designed for understanding, generating, and interacting with human language. These models are trained on extensive datasets containing text from books, articles, websites, and other sources to learn patterns, context, and semantics in language. LLMs are widely used in applications like chatbots, code generation, translation, summarization, and more. They are often built using transformer architectures and are central to the field of generative AI.
⚙️🦀 Build modular and scalable LLM Applications in Rust
Project Titania is a complete large language model system, from transformer to transistor, simple enough for one person to understand.
🦀 Decoder-only LLM built from scratch in pure Rust using Candle — no Python, no PyTorch. Gated DeltaNet + sparse attention, fine-grained MoE, native video/document understanding, long-horizon tool agents, quantization-aware training. Scales: Tiny (25M) to Large (1.3B).
Bones for your agents — composable async agentic AI framework for Rust
Ollama over LAN - Auto-discover your Ollama server on your local network with hassle-free ease.
Reprompt - Simple desktop GUI application to avoid writing the same prompts repeatedly.
A rust voice assistant which is was made to be easy to set up, customize and learn from.
Binary tensor format for more efficient storage format for multi-dimensional tensor data, commonly used in machine learning and deep learning applications.
A command line assistant that helps you with working with shell commands right from your terminal
GPT-2 Inference with tenferro
