“Model inference”

Route ClearerVoice-Studio tasks for ClearVoice inference, SpeechScore metrics, and speech-model training or data-preparation workflows.

Computational methods for statistical inference and optimization

Computer vision engineering workflow for dataset design, model selection (detection/segmentation/classification), evaluation, inference optimization, and…

C4 Model: Context, Container, Component, Code diagrams for architecture.

Synthesize a person's voice/persona from their content; cache it.

Route BiRefNet image segmentation, matting, inference, configuration, training, evaluation, and model-export workflows.

Statistical modeling toolkit.

Selects, deploys, and customizes AI models on Amazon SageMaker.

Create, revise, and review C4 model software architecture diagrams and supporting architecture documentation.

Hugging Face Hub CLI (hf) — search, download, and upload models and datasets, manage repos, query datasets with SQL, deploy inference endpoints, manage Spaces…

Implements the NOWAIT technique for efficient reasoning in R1-style LLMs.

Use when a task would benefit from a secondary model call through the local MCP tool lane, especially for Hugging Face or OpenAI-compatible inference…

Manage and fetch models from the Infip API.

Use when a CTF challenge centers on AI or LLM security rather than a conventional web, crypto, or reverse-only path.

World-class computer vision skill for image/video processing, object detection, segmentation, and visual AI systems.

GGUF format and llama.cpp quantization for efficient CPU/GPU inference.

Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching.

Provides guidance for enterprise-grade RL training using miles, a production-ready fork of slime.

Train Mixture of Experts (MoE) models using DeepSpeed or HuggingFace.

Scores binary predictions (Brier, log loss, ECE, MCE, AUROC, accuracy, reliability bins, per-cohort) or saved categorical outputs joined to retained targets…

Test availability, benchmark speed, and add a new model to any OpenAI-compatible provider in models.json.

QA financial models for formula errors, hardcodes, date logic, sign conventions, circularity, balance-sheet integrity, scenario switches, units, currencies…

Author the TLA+ abstract behavioural spec for an rd-flow workspace.

Guides the migration of existing AI workloads (Cloud Run, Gemini API, Gemini Enterprise Agent Platform) to self-hosted GKE inference using gcloud and kubectl.