Results for “pb-band”
8 skillsp-video
Generate videos using Pruna's optimized P-Video and WAN models via the inference.sh CLI, supporting text-to-video, image-to-video, audio input, and multiple resolutions.
584
pymc-python
Use for writing, reviewing, debugging, testing, or diagnosing Python Bayesian models built directly with PyMC, including Model, coords/dims, Data, random variables, potentials, posterior sampling, prior/posterior predictive checks, and InferenceData output. Trigger on model geometry, shape errors, divergences, sampler choice, mutable prediction data, and probabilistic validation. Do not use for Bambi formula models, NumPyro/JAX programs, ArviZ-only analysis of existing draws, deterministic optimization, or general statistics without PyMC code.
0 · bundle
developmental-band-translator
Tags harness-decomposed curriculum items (KUDs, LTs, criteria) with a school's developmental band metadata while preserving source voice and labels. Supply the band schema; the skill derives mapping rules from it.
0
matlab-model-ams-systems
Model a Phase-Locked Loop (PLL) IC from its datasheet or system specs using Mixed-Signal Blockset. Without this skill, agents universally select the wrong solver and produce non-functional PLL models — 100% of unguided attempts fail. Covers Integer-N, Fractional-N, Dual Modulus architectures, loop filter design, lock time optimization, VCO phase noise configuration, and msbPllArchitectures/msbPllFoundation block assembly. Use when: PLL modeling, frequency synthesizer design, phase noise simulation, lock time analysis, charge pump design, loop filter tuning, datasheet-to-model, Mixed-Signal Blockset PLL, msbPllArchitectures.
920 · bundle
pennylane
Train quantum circuits like neural networks with automatic differentiation, device-independent programming, and integration with PyTorch or JAX.
30.2k · bundle
pufferlib
Train reinforcement learning agents at millions of steps per second using optimized PPO, vectorized environments, and multi-agent support.
30.2k · bundle
matlab-model-via
Via modeling: pads, antipads, ground return vias, GRV placement, and signal integrity for high-speed layer transitions. TRIGGER: user asks to model a via, design a via transition, place ground return vias, analyze via performance, or check signal integrity through layer transitions. Invoke BEFORE writing code — only viaSingleEnded exists (no viaDifferential), and the location format is non-obvious. SKIP: general signal integrity without vias (use matlab-analyze-em), transmission line design (use matlab-design-pcb-transmission-line), PDN analysis (use matlab-analyze-pcb-pdn), material/stackup setup only (use matlab-manage-pcb-material).
920 · bundle
bbh-eval
Benchmarks zero-shot in-context learning on BIG-Bench Hard multiple-choice tasks, comparing self-generated demonstrations against direct prompting and chain-of-thought baselines, and reports accuracy.
3