This repository contains the LaWAM pretrained policy converted to the native LeRobot checkpoint format. Model parameters are stored in model.safetensors; loading this repository does not require the original PyTorch .pt checkpoint.

This is the pretrained LaWAM policy intended as an initialization checkpoint for downstream fine-tuning. The serialized default feature schema and processor statistics use the 7-dimensional Franka setup from the original release. Other robot embodiments require the downstream LeRobot dataset feature schema and normalization statistics to be supplied during fine-tuning.

The policy uses Qwen/Qwen3-VL-2B-Instruct as its portable base VLM identifier. The Qwen model is downloaded automatically unless base_vlm_path is overridden with a local copy.

LaWAM support requires the LeRobot integration from PR #3999 or a later LeRobot release containing that integration.

The checkpoint includes the LeRobot policy config, preprocessor, postprocessor, normalization tensors, and conversion provenance manifest.

The source checkpoint, source config, dataset statistics, LAM architecture config, and Qwen config/model were checked against their published SHA-256 values before conversion. A strict local from_pretrained() reload restored all 1,912 policy state keys while torch.load was disabled.