「tuning」の検索結果

Optimizes PostgreSQL queries, configures replication, implements advanced features including EXPLAIN analysis, JSONB operations, extension usage, and VACUUM tuning.

日本語の概要は準備中です。原文の説明を表示しています。

Fine-tunes LLMs and trains custom models using LoRA/QLoRA adapters, JSONL training datasets, hyperparameter configuration, RLHF, DPO, and model quantization.

日本語の概要は準備中です。原文の説明を表示しています。

Optimizes database queries and improves performance across PostgreSQL and MySQL systems including index design, query rewrites, configuration tuning, and partitioning strategies.

日本語の概要は準備中です。原文の説明を表示しています。

Discovers user intent and generates a structured, step-by-step plan for model customization workflows. This skill must always be activated alongside any other skill when the user's request relates to model customization — including fine-tuning, training, building, customizing, reviewing data, or getting advice on approach, regardless of domain. Do not skip this skill even if the immediate ask is narrow (e.g., reviewing data format or a single workflow step), because planning discovers the full scope of work needed. Also activate when the user wants to resume, continue, or modify an existing plan.

日本語の概要は準備中です。原文の説明を表示しています。

Design observability strategies: SLI/SLO frameworks, alerting, and dashboards. Use when instrumenting a production service, tuning alert rules, designing Grafana dashboards, defining SLOs and error budgets, or reducing alert fatigue.

日本語の概要は準備中です。原文の説明を表示しています。

Determines the organization's role (provider, deployer, importer, distributor, or quasi-provider) and assesses Art. 25 quasi-provider risk of the EU AI Act. This skill should be used when the user asks to "determine AI Act roles", "check if we are provider or deployer", "assess quasi-provider status", "check Art. 25 substantial modification", "check value chain responsibilities", or mentions "Betreiber", "Anbieter", "wesentliche Veränderung", or finetuning implications under the AI Act.

日本語の概要は準備中です。原文の説明を表示しています。

Use when auditing or recalibrating game balance: build a source-driven Monte Carlo balance lab (Rust + rayon) that extracts live game data, simulates human playstyles (AFK→pro), emits win-rate/economy verdicts with confidence intervals, and bruteforce-tunes parameters. Trigger on unfair levels, unreachable shops, farm exploits, interest-curve cliffs, post-content recalibration, or CI balance JSON diffs. Keywords: balance lab, Monte Carlo, win rate, difficulty curve, economy career, playstyle simulation, Resource extraction, GDScript parser, bruteforce tuning.

日本語の概要は準備中です。原文の説明を表示しています。

Universal Runtime best practices for PyTorch inference, Transformers models, and FastAPI serving. Covers device management, model loading, memory optimization, and performance tuning.

日本語の概要は準備中です。原文の説明を表示しています。

SCAIL-2 in-video character replacement on WAN 2.1. WanSCAILToVideo + SCAIL2ColoredMask + SAM3, the reference-image framing→scale rule, and the tuning/compositing pitfalls

日本語の概要は準備中です。原文の説明を表示しています。

Use when optimizing Godot games — profiler, draw calls, physics tuning, memory management, and common bottlenecks

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure Table Storage development including best practices, architecture & design patterns, limits & quotas, security, configuration, and integrations & coding patterns. Use when securing Table Storage, tuning telemetry, planning scale limits, designing keys, or scripting with PowerShell, and other Azure Table Storage related development tasks. Not for Azure Cosmos DB (use azure-cosmos-db), Azure Blob Storage (use azure-blob-storage), Azure Queue Storage (use azure-queue-storage).

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure Microsoft Opentelemetry development including configuration. Use when setting sampling, exporters, resource attributes, env vars, or tuning tracing/metrics behavior, and other Azure Microsoft Opentelemetry related development tasks. Not for Azure Monitor (use azure-monitor).

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure Managed Lustre development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and integrations & coding patterns. Use when mounting AML filesystems, linking Blob, using AKS CSI, setting quotas, or tuning Lustre performance, and other Azure Managed Lustre related development tasks. Not for Azure NetApp Files (use azure-netapp-files), Azure Virtual Machines (use azure-virtual-machines), Azure Virtual Network (use azure-virtual-network), Azure Virtual Network Manager (use azure-virtual-network-manager).

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure AI Personalizer development including troubleshooting, decision making, security, configuration, and integrations & coding patterns. Use when choosing single vs multi-slot setups, tuning policies/exploration, using apprentice mode, explainability, or local inference, and other Azure AI Personalizer related development tasks. Not for Azure AI Search (use azure-cognitive-search), Azure Machine Learning (use azure-machine-learning), Azure AI Metrics Advisor (use azure-metrics-advisor), Azure AI Anomaly Detector (use azure-anomaly-detector).

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure AI Metrics Advisor development including decision making, limits & quotas, security, configuration, and integrations & coding patterns. Use when configuring data feeds, tuning anomaly detection, managing alerts/hooks, or calling Metrics Advisor REST/SDKs, and other Azure AI Metrics Advisor related development tasks. Not for Azure AI Anomaly Detector (use azure-anomaly-detector), Azure Monitor (use azure-monitor), Azure Stream Analytics (use azure-stream-analytics).

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure Large Instances development including troubleshooting, limits & quotas, and integrations & coding patterns. Use when configuring Epic SKUs, sizing volume groups, tuning EHR storage, or resolving Epic–ALI connectivity/perf issues, and other Azure Large Instances related development tasks. Not for Azure Baremetal Infrastructure (use azure-baremetal-infrastructure), Azure Virtual Machines (use azure-virtual-machines), Azure Virtual Machine Scale Sets (use azure-vm-scalesets), Azure HPC Cache (use azure-hpc-cache).

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure Horizondb development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when tuning pgvector, azure_ai SQL functions, LangChain vector stores, Apache AGE graphs, or hybrid search, and other Azure Horizondb related development tasks. Not for Azure Cosmos DB (use azure-cosmos-db), Azure SQL Database (use azure-sql-database), Azure Table Storage (use azure-table-storage).

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure CycleCloud development including troubleshooting, best practices, decision making, architecture & design patterns, security, configuration, integrations & coding patterns, and deployment. Use when automating CycleCloud via API/CLI/SDK, configuring Slurm clusters, tuning HB/HC VMs, or securing access, and other Azure CycleCloud related development tasks. Not for Azure Batch (use azure-batch), Azure HDInsight (use azure-hdinsight), Azure Databricks (use azure-databricks), Azure Kubernetes Service (AKS) (use azure-kubernetes-service).

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure AI Immersive Reader development including best practices, limits & quotas, security, configuration, and integrations & coding patterns. Use when tuning read-aloud/translation, storing user prefs, Entra auth setup, JS SDK integration, or language support, and other Azure AI Immersive Reader related development tasks. Not for Azure AI Language (use azure-language-service), Azure AI Speech (use azure-speech), Azure Translator (use azure-translator), Azure AI services (use microsoft-foundry-tools).

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure DDoS Protection development including troubleshooting, best practices, decision making, architecture & design patterns, security, configuration, and integrations & coding patterns. Use when enabling DDoS IP/Network Protection, tuning policies, analyzing logs/metrics, or integrating NVAs and Azure Policy, and other Azure DDos Protection related development tasks. Not for Azure Firewall (use azure-firewall), Azure Firewall Manager (use azure-firewall-manager), Azure Web Application Firewall (use azure-web-application-firewall), Azure Virtual Network (use azure-virtual-network).

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure Data Api Builder development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when exposing DB objects via REST/GraphQL, tuning paging/timeouts, securing auth/RLS, or deploying DAB to Azure, and other Azure Data Api Builder related development tasks. Not for Azure API Management (use azure-api-management), Azure App Service (use azure-app-service), Azure Functions (use azure-functions), Azure Logic Apps (use azure-logic-apps).

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure Data Explorer development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when securing ADX (RBAC/MI), automating cluster/schema deploys, tuning ingestion/queries, or integrating via ODBC/JDBC/Power BI, and other Azure Data Explorer related development tasks. Not for Azure Synapse Analytics (use azure-synapse-analytics), Azure HDInsight (use azure-hdinsight), Azure Databricks (use azure-databricks), Azure Stream Analytics (use azure-stream-analytics).

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure Digital Twins development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when modeling DTDL graphs, integrating IoT Hub/ADx, configuring endpoints/routes, securing access, or tuning query units, and other Azure Digital Twins related development tasks. Not for Azure IoT Hub (use azure-iot-hub), Azure IoT Central (use azure-iot-central), Azure IoT Operations (use azure-iot-operations).

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure Functions development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when wiring Functions to HTTP/storage/queues, securing with VNets/MI, tuning scaling, or deploying via CI/CD, and other Azure Functions related development tasks. Not for Azure App Service (use azure-app-service), Azure Logic Apps (use azure-logic-apps), Azure Container Apps (use azure-container-apps), Azure Kubernetes Service (AKS) (use azure-kubernetes-service).

日本語の概要は準備中です。原文の説明を表示しています。