Claude Skills by VectorSpaceLab

"Use Stability AI's generative-models package for SDXL inference

"Use and adapt generative-models demo UI routes and invisible

"Use the installed sgm.inference.api Python API for SDXL

"Author, inspect, adapt, and troubleshoot config-driven training

"Run, adapt, and troubleshoot standalone SVD, SVD-XT, SV3D, SV4D,

"Use Stable-Baselines3 for PyTorch reinforcement learning: train

"Create and validate Gymnasium custom environments for

"Evaluate Stable-Baselines3 policies, configure callbacks/logging,

"Customize Stable-Baselines3 policies, feature extractors,

"Choose and train Stable-Baselines3 algorithms, instantiate

"Routes Stable Diffusion video, image, audio-synced interpolation,

"Routes Stable Diffusion walk, music-video, still-image,

"Routes Gradio Interface launch, example app adaptation, and UI

"Use and maintain AUTOMATIC1111 Stable Diffusion WebUI workflows,

"Build and validate Stable Diffusion WebUI REST API calls for

"Manage Stable Diffusion WebUI checkpoints, VAEs, embeddings,

"Author, debug, and package stable-diffusion-webui scripts and

"Launch Stable Diffusion WebUI safely in UI, API, and API-only

"Use textual inversion and hypernetwork create/train endpoints,

"Routes Stanford Alpaca instruction-data, Self-Instruct generation,

"Guides Stanford Alpaca dataset schema, prompt formatting, label

"Supervised fine-tuning of LLaMA/OPT-style causal LMs with Alpaca

"Guide Self-Instruct-style instruction data generation with prompt

"Guide Alpaca weight-diff creation and recovery, path-role

"Use Stanza for neural NLP pipelines, CoreNLP client workflows,

"Operate Stanza's CoreNLP client, Java server lifecycle, pattern

Manipulate Stanza Documents and CoNLL-U safely.

"Operate Stanza pipelines, multilingual routing, resource

"Guide safe Stanza training, evaluation, and dataset preparation

"Safely adapt Stanza demos and visualization workflows into scripts

"Operate StarVLA for vision-language-action model development,

"Plan StarVLA simulation benchmark evaluations and two-environment

"Integrate LeRobot-format StarVLA datasets, modality schemas, robot

"Choose and inspect StarVLA model frameworks, registry names,

"Serve StarVLA checkpoints over websocket or GR00T-compatible ZMQ

"Plan StarVLA training, co-training, YAML overrides, DeepSpeed

"Self-contained operating guidance for StarDist 0.9.2: CPU-verified

"Use for StarDist 2D workflows: Config2D data contracts, training

"Route StarDist 3D users through Config3D, ray and anisotropy

"Route StarDist file prediction, local-model loading, BioImage.IO

"Route StarDist label validation, star-distance representations,

"Use Nixtla StatsForecast for statistical time-series forecasting,

"Operate normal StatsForecast pandas/polars panel forecasting

"Use local parallel and optional Dask/Ray/Spark StatsForecast

"Generate StatsForecast synthetic fixtures, MSTL trend/seasonal

Choose and configure StatsForecast model classes and direct model APIs.

"Use statsmodels for statistical modeling, econometrics,

"Use statsmodels datasets, result objects, predictions, summaries,

"Use statsmodels source-development guidance for Meson/Cython

"Use statsmodels discrete choice and count model APIs for Logit,