Total 57,055 skills, AI & Machine Learning has 9485 skills
Showing 12 of 9485 skills
Brev instance operating guidance for NeMo-RL agents working in /home/ubuntu/RL with limited workspace disk, a larger /ephemeral volume, and optional /home/ubuntu/RL/.env secrets. Use when running nemo-rl-auto-research campaigns, experiments, training jobs, model or dataset downloads, shared cache-heavy commands, log-producing runs, checkpoint generation, W&B or Hugging Face authenticated workflows, or any workflow that may create large files on Brev.
The house format and rules for writing or updating an agentmemory skill. Use when adding a new skill, restructuring an existing one, or reviewing a skill contribution for consistency.
Fine-tune any HuggingFace CV / VLM / LLM model on local NVIDIA GPUs inside an NGC PyTorch container. Use when the user wants to fine-tune a HuggingFace model (full or LoRA), train a vision / VLM / LLM model end-to-end, generate a reproducible HF training pipeline, smoke-test a HuggingFace model locally before scale-up, push a fine-tuned model to the HF Hub with a model card, or emit a self-contained rerun skill for an existing HuggingFace finetune. Supports image classification, object detection, semantic / instance / panoptic segmentation, depth estimation, image-text-to-text VLM (SFT / LoRA), and LLM SFT / DPO / GRPO. Six-step workflow: inspect and qualify, hardware and NGC image, research, generate and smoke, train + eval + infer, push and emit rerun skill.
PyTorch-based TAO image classification. Supports a wide range of backbones (FAN, EfficientNet, ResNet, etc.) with distillation and quantization for deployment. Use when training, evaluating, distilling, quantizing, exporting, or running inference for a TAO image-classification (PyT) model. Trigger phrases include "train image classifier", "TAO classification", "ResNet/EfficientNet/FAN backbone classifier", "classification-pyt".
Playbook for launching, monitoring, stopping, and debugging NeMo-RL recipes on a Kubernetes cluster via the nrl-k8s CLI. Covers ephemeral vs long-lived RayCluster modes, iterating on runs, and debugging hung or failed training jobs.
Build and run FastFold BoltzGen protein-design workflows end-to-end through API or Composer draft links. Use this whenever users mention BoltzGen, design-spec YAMLs, binder design, multi-spec scaffold workflows, CIF/PDB preparation, workflow graph upsert, `/workflow/composer/<id>`, candidate metrics/structure results, or ask naturally for "help me design a protein" / "give me a simple example".
Generate AI videos with Luma Dream Machine via AceDataCloud API. Use when creating videos from text prompts, generating videos from reference images, extending existing videos, or any video generation task with Luma. Supports text-to-video, image-to-video, and video extension.
Access 50+ LLM models through AceDataCloud's unified chat APIs. Use when you need OpenAI-compatible chat/responses calls or the newer `/aichat2/conversations` API across GPT, Claude, Gemini, Grok, Kimi, GLM, and DeepSeek models. Supports streaming, multimodal input, and tool calling.
Describes the agent skills shipped with NemoClaw and how to access them by cloning the repository. Use when users ask about AI agent support, coding assistant integration, or the .agents/skills/ directory. Trigger keywords - nemoclaw agent skills, ai coding assistant, cursor, claude code, copilot.
Inspects sandbox health, traces agent behavior, and diagnoses problems. Use when monitoring a running sandbox, debugging agent issues, or checking sandbox logs. Trigger keywords - monitor nemoclaw sandbox, debug nemoclaw agent issues.
Experiment with configs by creating and managing variations. Helps you test different models, prompts, and parameters to find what works best through systematic experimentation.
Apply trader Serenity's (@aleabitoreddit) AI/semiconductor supply-chain analytical lens to US-stock ideas and market judgment. Use this skill whenever evaluating a stock decision (buy / sell / hold / size); forming an outlook on any AI, semiconductor, optical/CPO, memory, power/grid, or neocloud name; mentioning any ticker in Serenity's universe (NBIS, AXTI, LITE, SIVE, COHR, AAOI, IREN, CRWV, MU, SNDK, NVDA, TSM, MRVL, AVGO, INTC, SOI, IQE, TSEM, CIFR, XLU, VST, CEG, EWY, etc.); asking "what would Serenity think", "is this a real bottleneck", or wanting a supply-chain / bottleneck read on a thesis. Decision-support only — never auto-trades and never places or cancels orders.