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Found 44 Skills
Install cuOpt for Python, C, or server via pip, conda, or Docker; verify the install. For building cuOpt from source, see cuopt-developer.
Stateful LLDB debugging via LLDB Python API
FastAPI Python async framework with Pydantic and automatic OpenAPI. Use for Python APIs.
One-click model liberation toolkit for removing refusal behaviors from LLMs via surgical abliteration techniques
Trains, validates, tests, and runs prediction for Physical AI Studio policies via the library Lightning stack. Use when running physicalai fit/validate/test/predict, calling physicalai.train.Trainer and Policy APIs from Python, writing or editing YAML configs under library/configs, wiring a model + datamodule + trainer, resuming from a checkpoint, or debugging a training run. Covers ACT, Pi0, Pi0.5, GR00T, and SmolVLA.
Train a computer-vision model with the getitune library (the Geti training library) using its Python API or CLI. Use when a user wants to train, fine-tune, or evaluate a model with `create_engine(...)` and `engine.train()/engine.test()`, run `getitune train`/`getitune test`, pick or override a recipe under `getitune.recipe.<task>`, choose a device (cpu/gpu/xpu/cuda), warm-start from a checkpoint, or debug a training run. Covers classification, detection, instance/semantic segmentation, and keypoint detection.
Write and run ArcGIS API for Python code in ArcGIS Notebooks or a local environment. Use when the user works with the arcgis package, a hosted ArcGIS Notebook runtime, ArcPy in a notebook, or deletes or overwrites hosted data from Python.
US options data: chain snapshots, contracts, trades, quotes, greeks, IV, OI. Use when pulling option chains or contract metrics for analysis (e.g. AAPL Jan calls, SPY chain, NVDA IV, weekly puts).