Results for “nemotron”

Routes NVIDIA Nemotron Speech (Riva) NIM tasks for ASR, TTS, and NMT, covering cloud-hosted inference, self-hosted Docker deployment, and custom model builds.

Selects Jetson-compatible containers, vLLM runtime images, and Jetson AI Lab PyPI indexes based on Orin SM 8.7 vs Thor SM 11.0 and JetPack version.

Build and deploy web servers anywhere using Nitro's filesystem routing, caching, tasks, WebSockets, and deployment presets for Node.js, Bun, Deno, Cloudflare, Vercel, and more.

NVIDIA NemoClaw plugin for secure sandboxed installation and orchestration of OpenClaw always-on AI assistants via OpenShell

Use when building a cursor trail whose spacing stays constant at any hand speed by emitting motes per distance travelled (not on a timer)—sub-segment placement, ring-buffer ordering, idle breath, 3D screen anchoring, coasting, touch and reduced-motion fallbacks—for wisps, sparks, embers, comet tails, plankton, or dust.

Builds and trains deep learning models with PyTorch, including tensors, autograd, and neural network modules.

Lint and format Python code for Megatron-LM using ruff, black, isort, pylint, and mypy, with commands for autoformatting and import ordering.

Launch distributed Megatron-LM training jobs on a SLURM cluster with a minimal sbatch skeleton, environment-variable setup for torch.distributed.run, CUDA_DEVICE_MAX_CONNECTIONS rules, container conventions, monitoring, and per-rank failure diagnosis.

Analyze AI disruption pressure across a business, map competitive exposure, and produce a 90-day defensive action plan.

Analyze AI disruption pressure across a business, map competitive exposure, and produce a 90-day defensive action plan.

Analyze AI disruption pressure across a business, map competitive exposure, and produce a 90-day defensive action plan.

Analyze AI disruption pressure across a business, map competitive exposure, and produce a 90-day defensive action plan.

Analyze AI disruption pressure across a business, map competitive exposure, and produce a 90-day defensive action plan.

Detect monorepo structure, identify shared chokepoints, and generate safe parallel lane specs aligned to package boundaries

MONOPOLY is a Senior System Design Engineer skill for architecting, reviewing, and scaling systems. Triggers on requests involving architecture, databases, scaling, microservices, or infrastructure de

KOMODO v1.0 — Momentum Event Consensus. Uses leaderboard_get_momentum_events (real-time threshold crossings) to detect when 2+ quality SM traders cross momentum thresholds on the same asset/direction within 60 minutes. Confirmed by market concentration + volume. Enters with the momentum. Replaces MANTIS v1.0 and SCORPION v1.1 (both used stale position data).