Fine-tune Parakeet TDT v2 on clinical vocabulary using NeMo, then compare key-term error rates before and after training. The results guide whether to keep the model, expand the dataset, or prepare it for deployment.
Continue training a KERMT molecular model on a custom SMILES corpus, where text strings describe molecular structures. The skill validates data and checkpoints, prepares training inputs, and launches containerized training with saved logs and checkpoints.
Fine-tune a pretrained KERMT model on a CSV of molecular structures and labeled targets. The workflow checks inputs, prepares features, launches training in a container, and saves trained models, logs, and test results.
Build DeepStream commands for image and video inference, object detection, tracking, and streaming. The skill asks about missing requirements, assembles a GStreamer processing pipeline, and checks its syntax, components, properties, and connections where supported.
Generate drug-like molecule candidates with GenMol NIM through NVIDIA's hosted API or local Docker deployment. Expand molecular scaffolds, modify existing candidates, rank results by drug-likeness or lipophilicity, and save the ranked molecules to a file.
Prepare the KERMT environment by checking Docker and GPU access, building the local container image when needed, and testing whether PyTorch detects GPUs inside it. Report the image details and detected GPU count before other KERMT workflows begin.
Predict how small molecules may bind to proteins using DiffDock through NVIDIA NIM. Prepare molecular inputs, run hosted API or local Docker requests, and save ranked binding poses with confidence scores for inspection.
Measure and tune a DeepStream video pipeline using Nsight Systems. The skill benchmarks inference batch sizes, derives configuration settings from measurements and GPU limits, and reports FPS, processing bottlenecks, and available timings for individual processing components.
Monitor KERMT jobs running in the background by reading run records, Docker container status, and logs. Summarize training progress and validation metrics, stream logs, or report final test metrics when a finetune run completes successfully.
Check one DICOM medical imaging series before conversion or AI inference by inspecting headers only. Produce a JSON report with file inventory, image orientation, personal information flags, findings, and a pass, warn, or fail verdict.
Extend an existing grover_base model with a new decoder that reconstructs molecular structure strings, then continue pretraining on your corpus. The workflow validates inputs, rebuilds vocabulary components, and records the conversion and training outputs.
Integrate a supported object detection model from HuggingFace or NVIDIA NGC into NVIDIA DeepStream. Automates model acquisition and conversion, TensorRT engine building, detection output parsing, multi-stream performance benchmarks, and reports with charts in Markdown, HTML, and PDF.
Move pandas-style table processing to NVIDIA GPUs using cuDF. Choose minimal-change acceleration or explicit GPU code, handle joins and aggregations, compare results with pandas, and use dask-cuDF when data exceeds GPU memory.
Explore competing goals such as cost and service quality through repeated cuOpt solves. Organize efficient alternatives into a Pareto frontier, a set of tradeoff choices, and explain what each improvement costs in another objective.
Install cuOpt for Python, C, or use as a REST server, a service called over HTTP. Choose pip, conda, or Docker to match the environment, verify installation, and troubleshoot package or CUDA mismatches.
Customize NVIDIA Nemotron Voice Agent’s Generic Pipecat example for appointment scheduling, five-field patient intake, or a custom healthcare conversation. Build prompts and tool handlers without a separate backend, then validate conversation behavior, services, and voice interaction.
Calibrate multiple cameras from recorded MP4 files through the AutoMagicCalib REST API. The skill handles project creation, uploads, input verification, progress checks, and evaluation when reference data is supplied, with optional VGGT refinement.
Convert a single CT DICOM series into a NIfTI volume with Hounsfield units, the CT intensity scale. A JSON summary records image dimensions, spacing, orientation, and the coordinate transformation matrix for checking the conversion.
Generate molecular predictions from a CSV of SMILES strings, a text notation for molecular structures, using a finetuned KERMT model. Validate inputs, clean data, compute molecular features, and return predictions with execution logs and a replay command.
Create a Python configuration for generating synthetic datasets with the Data Designer library. Describe the data you need, then refine requirements interactively or let the agent choose assumptions and assemble the generation pipeline.
Write and debug nvMolKit Python code for processing large molecule batches on GPUs. Covers molecular fingerprints, compact representations of molecular features, plus similarity calculations, 3D conformer generation, optimization, clustering, and molecular searches using RDKit objects.
Generate and screen small-molecule drug candidates with three NVIDIA BioNeMo NIM services. Use GenMol to create molecules, DiffDock to predict how they fit a target protein, and Boltz2 to estimate binding strength and rank candidates.
Write, review, and migrate DALI data processing code using dynamic mode, which calls operators directly from ordinary Python. Handle readers, batches, GPU processing, PyTorch conversion, random state, and checkpoints with the conventions specific to this API.
Evaluate speech recognition on synthetic clinical audio listed in a NeMo manifest. Produce four error metrics and a five-section report highlighting missed medical terms, then use pronunciation and noise breakdowns to guide dataset improvements or fine-tuning decisions.
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