executing-plans
executing-plans
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available
florence-2Use Maestro Florence-2 for fine-tuning command/API construction, checkpoint load/save, inference, object-detection formatting, LoRA/freeze/none choices, and troubleshooting.
Independent GitHub snapshot · Automated classification · Original documentation governs
Use this sub-skill when the task is specifically about Maestro's Florence-2 integration: maestro florence_2 train, the maestro.trainer.models.florence_2 Python APIs, Florence-2 checkpoint loading/saving, inference calls, or the Florence object-detection text format.
<OD> prefix and the Florence <loc_*> suffix rules in detection formats.microsoft/Florence-2-base-ft.refs/pr/20.lora, freeze, and none. Do not use or recommend qlora for Florence-2 in Maestro.<OD> and suffix fragments of the form class<loc_xmin><loc_ymin><loc_xmax><loc_ymax> with coordinates normalized to the 0..1000 range.From the generated Maestro skill tree, run:
python sub-skills/florence-2/scripts/smoke_florence_detection_format.py --help
python sub-skills/florence-2/scripts/smoke_florence_detection_format.py --json
These checks import only Maestro's Florence detection formatter functions and NumPy. They do not open datasets, call Roboflow, contact Hugging Face, download weights, or start training.