Results for “part-number”

Runs NV-Segment-CTMR segmentation on CT or MRI NIfTI volumes and records label-map evidence.

SA-1B: Segment Anything 1 Billion Masks Dataset

Segment any object in images using points, boxes, or masks as prompts, or automatically generate all object masks with zero-shot transfer.

Segments abdominal organs from CT NIfTI volumes using the NV-Segment-CT VISTA3D model, producing label maps and structured evidence JSON.

Foundation model for image segmentation with zero-shot transfer. Use when you need to segment any object in images using points, boxes, or masks as prompts, or automatically generate all object masks in an image.

Foundation model for image segmentation with zero-shot transfer. Use when you need to segment any object in images using points, boxes, or masks as prompts, or automatically generate all object masks in an image.

Computes the Recall metric using torchmetrics, including configuration for binary, multiclass, and multilabel tasks.

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.

Perform fast genomic interval operations (overlap, nearest, merge, coverage, cluster, complement, subtract, count-overlaps), multi-format bioinformatics I/O, DataFusion SQL, and pileup on Polars DataFrames via the polars-bio library, serving as a scalable alternative to bioframe and bedtools.

Foundation model for image segmentation with zero-shot transfer. Use when you need to segment any object in images using points, boxes, or masks as prompts, or automatically generate all object masks in an image.

Turn "can we even hit this number" into a capacity model that shows the truth before the quarter does. Models ramped-rep productivity, builds the hiring plan the target requires, states the ramp assumptions plainly, and names the gap between plan and capacity so nobody discovers it in month three. Built for B2B sales and RevOps leaders, customizable to your ramp and your CRM. Trigger on "build a capacity model", "how many reps to hit the number", "what's the hiring plan", "are we capacity constrained", "model the ramp", or any capacity or headcount planning question.

Tworzenie i konfiguracja definicji elementów wynagrodzenia na platformie Soneta przez MCP soneta_ui. Algorytmy naliczania (kreator, edytor C#, wbudowane), wzorce algorytmiczne, receptury kodu C# dla elementów płacowych, konfiguracja PIT/ZUS/nieobecności. Używaj gdy użytkownik: (1) chce utworzyć/skonfigurować definicję elementu wynagrodzenia (zakładki Ogólne, Deklaracje, Nieobecności, Algorytm); (2) pyta o algorytm naliczania (kreator, edytor, kod C#); (3) potrzebuje kodu C# do edytora algorytmu (_Param, _Wylicz, _Wartość1h); (4) pyta o wzorce dla dodatków, nieobecności, zasiłków; (5) wspomina 'definicja elementu', 'element wynagrodzenia', 'algorytm płacowy', 'WypSkladnik', 'WypElement', 'premia procentowa', 'dodatek stażowy', 'zasiłek chorobowy', 'ekwiwalent za urlop'; (6) pisze recepturę kodu płacowego (staż pracy, wymiar etatu, czas pracy, wskaźniki, cechy pracownika).

Fixes common PyTorch bugs including percentile calculations, LayerNorm for Conv1d, and buffer edge cases in reinforcement learning and neural network code.