Open-Weight Models

This repository groups five full-parameter RL checkpoints in separate subdirectories. Each subdirectory is a self-contained Hugging Face BF16 inference model with weights, tokenizer, a model card, training configuration, export validation and SHA256 checksums. The repository root is a collection, not a model checkpoint. Specify subfolder for both the model and tokenizer: Tested export/loading versions and a short generation example are recorded in each model directory. Agent evaluation requires the accompanying tool harness, prompts, corpus/index and judge protocol; loading the weights alone does not reproduce the reported QA score. - All five checkpoints use full-parameter RL, not RL LoRA…

A 31.9M-parameter Llama-architecture causal language model trained from scratch to reconstruct particle-track parameters from detector hit patterns, treating track fitting as a language translation problem: an array of encoded hit positions is translated into a short domain-specific "call" that regenerates it. A detector stack has 12 layers, each with 32 strips. A charged particle (e.g. a cosmic muon) crosses the stack roughly in a straight line, hitting strip round(slp layer + icpt) in every layer it geometrically passes through (slp = slope in strips/layer, icpt = intercept in strips). Each hit is encoded as a single integer layer 32 + strip in [0, 383]. - add — spurious hits not on the…

Official model checkpoints for the solution in the Traffic Sign Recognition under Adverse Weather Competition. See classes.txt for the 25 traffic sign classes. For inference scripts, training code, and in-depth engineering retrospective, visit the GitHub Repository.

π₀.₅ (Pi05) is a Vision-Language-Action model from Physical Intelligence designed for open-world generalization: it evolves π₀ to generalize to entirely new environments and situations that were never seen during training. The LeRobot implementation is adapted from their open-source OpenPI repository. This policy has been trained and pushed to the Hub using LeRobot. Learn how to train and run it in the LeRobot pi05 guide, or browse the full documentation. The policy consumes these observation features and produces these action features. Inputs Outputs New to LeRobot? These guides cover the full workflow: - Install LeRobot — set up the lerobot package. - Hardware setup — assemble, wire, and…

π₀.₅ (Pi05) is a Vision-Language-Action model from Physical Intelligence designed for open-world generalization: it evolves π₀ to generalize to entirely new environments and situations that were never seen during training. The LeRobot implementation is adapted from their open-source OpenPI repository. This policy has been trained and pushed to the Hub using LeRobot. Learn how to train and run it in the LeRobot pi05 guide, or browse the full documentation. The policy consumes these observation features and produces these action features. Inputs Outputs New to LeRobot? These guides cover the full workflow: - Install LeRobot — set up the lerobot package. - Hardware setup — assemble, wire, and…