Built with DINOv3. This is the completed V2 mean-pooling model for 2,991 plant species from Western Australia. Supply one photo, or 2–4 distinct photos from the same plant observation. This release uses the epoch-12 EMA weights from the expanded-data BF16 training run. The CLI uses self-contained TorchScript graphs (encoder.ts and classifier.ts) and imports no project modules. FP32 model.safetensors is also included for research use. Optimizer state and training data are excluded. executorch/PlantDetect-WA-V2-INT8.pte is a W8A8 export of this mean-pooling checkpoint for CPU inference without PyTorch. It uses custom plantquant:: kernels (INT8 weights with per-output-channel FP32 scales, FP16…