AI tools built with Python

Dynamic continual learning model trained on 8GB VRAM

mini-AGI is a byte-level language model that trains from scratch on a single 8 GB VRAM GPU and keeps learning from a continuous stream of text. Weights live on disk and are paged onto the GPU as needed, so model size is bounded by disk spac

💬 0Y▲ 277 on HNLLMs & InfrastructureResearch & DataOpen Sourceby AI Launch Team

Distill Jev into a local model – with a disagreement bound

Jevstiller distills a hosted Jev classifier into a local model, with a measured bound on how often the local model disagrees with Jev. It runs as a drop-in proxy, so batch jobs avoid a network call per answer while keeping answers close to

💬 0Y▲ 63 on HNLLMs & InfrastructureOpen Sourceby AI Launch Team

Replacing LLM judges with typed Jev decisions

jevals runs evals and guardrails for AI agents using Jev-style decision models instead of an LLM judge. All the checks for a trace, such as tool choice, groundedness, answer relevancy, prompt injection and PHI, go out as one request that co

💬 0Y▲ 47 on HNLLMs & InfrastructureAI AgentsOpen Sourceby AI Launch Team

High-Performance Serving Runtime for Robotics Models

InstinctFlash is a high-performance serving framework for robotics models from General Instinct (YC P26). It serves eight robotics model families, including pi05, LingBot-VLA, LingBot-VA and GR00T N1.7, through one runtime with Python and W

💬 0Y▲ 27 on HNLLMs & InfrastructureOpen Sourceby AI Launch Team