333 skills · sorted by relevance
Launch machine learning training jobs on local or remote GPUs. The skill checks available GPU memory, synchronizes code, saves logs, and verifies startup, with optional experiment tracking and support for Vast.ai and Modal.
Develop mathematical proofs for machine learning and AI theory by checking assumptions, intermediate results, and edge cases. Produce a complete proof, a corrected claim with its proof, or a report explaining the unresolved gap.
Launch machine learning experiments on local GPUs, remote servers, Vast.ai, or Modal. It checks the configured environment, deploys code, saves logs, and verifies startup, with optional W&B metric logging and automatic Vast.ai result collection and instance cleanup.
Run batches of machine learning experiments on remote GPUs over SSH, varying settings and random seeds. The skill schedules jobs, tracks progress, retries GPU memory failures, and cleans up leftover sessions before starting subsequent batches.
Compare machine learning experiment results from JSON or CSV files. Calculate improvements over a baseline, summarize variation across repeated runs, identify trends and unusual results, and suggest experiments to test possible explanations.
Plan ablation studies, experiments that remove or replace parts of a machine learning method to test their contribution. Define reviewer questions, expected outcomes, priorities, execution order, and compute estimates, then implement experiments and record findings.
Track machine learning experiments with SwanLab by recording training settings, metrics, and media such as images and audio. Learn to compare runs, inspect training charts, and connect existing training code to local, cloud, or self-hosted dashboards.
Set up W&B to record machine learning metrics and settings, visualize training progress, and compare experiments. Includes automated searches for training settings, version tracking for datasets and models, and shared reports for team collaboration.
Creates figures for machine learning papers from draft text or experiment data. Extracts components for Gemini-generated diagrams, chooses suitable charts with matplotlib or seaborn, and adjusts colors, fonts, and export formats for publication.
Manage machine learning experiments with MLflow by recording settings, metrics, files, and trained models. Covers experiment comparison, model version management, reproducible project configurations, and deployment workflows across local and cloud environments.
Guides setup and operation of Lambda Labs GPU instances for machine learning training and inference. Covers SSH access, persistent storage, API automation, and multi-GPU or multi-node training, including how to retain checkpoints and terminate idle instances.
Build JavaScript or TypeScript applications that run text, image, and audio models in browsers or server runtimes. Guides compatible model selection, GPU or CPU execution, caching, and memory cleanup without requiring a Python server.
Track machine learning experiments with Trackio by recording training measurements, viewing live dashboards, and flagging diagnostic events. Retrieve metrics and alerts through command-line queries, with JSON output for automated monitoring and experiment review.
Draft and revise machine learning, computer vision, and natural language processing papers. Improve section structure, paragraph flow, and figures or tables, then check major claims against experimental evidence and review the draft from a skeptical reviewer’s perspective.
Find GitHub projects using keywords, minimum stars, and update dates, then collect repository details and contributor profiles through BrowserAct. Results include project descriptions, contributor biographies, personal websites, and Twitter handles for research, recruiting, or collaboration scouting.
Add datasets, models, and other components to machine learning projects using consistent registration and creation patterns. The skill guides file placement, configuration, and automatic module loading so new components fit the project's established architecture.
Guide bug bounty work from asset discovery to validation and reporting, while resolving local locations of security tools, wordlists, and cloned projects. It covers web and AI security testing with an emphasis on demonstrated impact.
Develop and check research code in MATLAB/Octave or Python for signal processing, image analysis, statistics, and simulations. This skill supports reproducible workflows, checks units and assumptions, and prepares figures for papers and presentations.
Turn machine learning research code and experimental results into conference paper drafts. Organize claims and evidence, find related studies, verify references through academic services, and adapt manuscripts using LaTeX templates and submission checklists.
Add datasets, models, and other components to machine learning projects using consistent registration and creation patterns. The skill guides file placement, configuration, and automatic module loading so new components fit the project's established architecture.
Create figures for machine learning papers from text or experiment data. Uses Gemini for architecture diagrams and matplotlib/seaborn for numerical charts, choosing suitable layouts and chart types while preparing consistent styling, export files, and reusable generation scripts.
Helps plan dataset splits for machine learning training, validation, and testing. Specifies ratios, random seeds, class balance rules, and time or group constraints, with guidance for handing the split to leakage review and model training.
Set up W&B to record machine learning metrics and settings, visualize training progress, and compare experiments. Includes automated searches for training settings, version tracking for datasets and models, and shared reports for team collaboration.
Build PyTorch machine learning workflows for molecules, proteins, and biomedical relationships. Get guidance on datasets, model selection, training, and evaluation for property prediction, protein modeling, molecule generation, and planning synthesis routes from target molecules.