「tune」の検索結果

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

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Selects a fine-tuning technique (SFT, DPO, RLVR, or RLAIF) for the user's use case and validates it against the selected model's available recipes. Use when the user has decided to finetune and needs to choose a technique, or when the technique needs to be validated against a model. Requires a base model to already be selected (via model-selection skill).

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。

Generates code that deploys fine-tuned models from SageMaker Serverless Model Customization to SageMaker endpoints or Bedrock. Use when the user says "deploy my model", "create an endpoint", "make it available", or asks about deployment options. Identifies the correct deployment pathway (Nova vs OSS), generates deployment code, and handles endpoint configuration.

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This skill should be used when the user asks to "decide reasoning effort", "set a thinking budget", "when to use extended thinking", "tune reasoning vs cost", or "should this task use a reasoning model".

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。

Tune eval thresholds: dimension minimums, weights, auto-reject floors. "raise the hallucination threshold"

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Generate a spreadsheet of test entries — newly designated names from OFAC, OFSI, and EU sanctions lists plus deliberate variations of those names — to validate that a sanctions screening system catches fresh designations and is tuned to the right fuzziness threshold. Use this whenever the user asks for sanctions list update test data, screening regression test data, screening QA, fuzzy match calibration, or wants to verify their screening lists are current. Trigger even if the user doesn't say 'screening' explicitly — phrases like 'test my sanctions list', 'check our SDN coverage', 'is my list up to date', or 'build me a regression set from the latest designations' should also invoke this skill.

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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.

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Build Qwen Image 2512 text-to-image workflows with QwenImageIntegratedKSampler, separate component loading, lightning LoRAs, and fine-tuned model variants

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Run the ComfyUI agent locally for FREE with no subscription, no API key, and fully offline, using our gemma4 models fine-tuned on the comfyui-mcp tool suite via Ollama. Use when the user asks about running locally, running for free, offline use, avoiding API costs, Ollama setup, or which local model to pick.

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A post hoc cell type classification tool to fine-tune cell type annotations generated by any cell type classification procedure with semi-supervised learning algorithm AdaSampling technique. The current version of scReClassify supports Support Vector Machine and Random Forest as a base classifier.

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Expert knowledge for Azure Portal development including troubleshooting, security, and configuration. Use when managing portal RBAC sharing, Intune/Entra mobile access, dashboard JSON, portal policies, or HAR diagnostics, and other Azure Portal related development tasks. Not for Azure Cloud Shell (use azure-cloud-shell), Azure Resource Manager (use azure-resource-manager), Azure Monitor (use azure-monitor), Azure Security (use azure-security).

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Provides guidance for writing and benchmarking optimized Triton kernels for AMD GPUs (MI355X, R9700) on ROCm, targeting HuggingFace diffusers (LTX-Video, SD3, FLUX) and transformers. Core kernels: RMSNorm, RoPE 3D, GEGLU, AdaLN. Includes XCD swizzle, autotune, diffusers integration patterns, and LTX-Video pipeline injection.

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Export your entire Prospeo people search to CSV. Build filters in Prospeo's UI, then use this skill to extract every result via the API — even searches over 25K. Handles pagination, rate limiting, deduplication, and state-by-state splitting automatically. Pair with /icp-prompt-builder on a 50-person sample to tune a qualification prompt BEFORE exporting 25K.

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Interactive loop that builds and tunes an AI prompt for evaluating whether a company fits a client's ICP. Run after any list-building skill (disco-like, blitz-list-builder, google-maps-list-builder, prospeo-full-export) to qualify companies before scaling. Iterates batches of 10 companies with user feedback, stops when 2 consecutive rounds have zero corrections, saves the final prompt for reuse. Always uses Claude Code Task sub-agents — never an external API key.

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Customise the prd-taskmaster plugin workflow via curated brainstorm questions. The AI asks, the user answers in plain English, and the skill writes their preferences to .atlas-ai/config/atlas.json. Future runs of prd-taskmaster read that file and apply user preferences to phase gates, validation strictness, default provider, preferred execution mode, and template choice. For deeper tweaks beyond the curated questions, users can hand-edit files in .atlas-ai/customizations/. Use when the user says "customise workflow", "customize workflow", "adjust my PRD settings", "tune the skill", or wants to change how prd-taskmaster behaves.

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扮演中国古代算命先生，结合八字命理，根据用户提供的生辰八字推演性格、五行、事业、财运及感情运势，语气古风且神秘。

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。

Return brief playful positive, neutral or negative fortune game responses. Use for this Bot Generator Bot template; creates drafts or simulations within its declared scope.

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。

Containerize NestJS apps with multi-stage Docker builds, tune Node.js memory, and implement graceful shutdown hooks. Use when writing Dockerfiles, configuring K8s deployments, or adding shutdown hooks for NestJS.

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Universal skill diagnosis and optimization tool. Detect and fix skill execution issues including context explosion, long-tail forgetting, data flow disruption, and agent coordination failures. Supports Agy CLI for deep analysis. Triggers on "skill tuning", "tune skill", "skill diagnosis", "optimize skill", "skill debug".

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Train or fine-tune SentenceTransformer bi-encoders, CrossEncoder rerankers, or SparseEncoder models, including losses, negatives, evaluation, distillation, LoRA, and Matryoshka. Use for sentence-transformers training tasks.

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Train and fine-tune transformer language models using TRL (Transformers Reinforcement Learning). Supports SFT, DPO, GRPO, KTO, RLOO and Reward Model training via CLI commands.

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Train or fine-tune language models with TRL or Unsloth on Hugging Face Jobs, including SFT, DPO, GRPO, reward models, and GGUF conversion. Use for cloud LLM training; use huggingface-vision-trainer for vision tasks.

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AI-powered paywall optimizasyon. Sektore gore otomatik analiz, A/B test senaryolari, churn prediction sinyalleri, push notification stratejileri, agresif satis teknikleri ve RevenueCat Experiments entegrasyonu. paywall-strategy, revenuecat-patterns ve subscription-pricing skill'lerinin ustune insa eder.

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Graph database implementation for relationship-heavy data models. Use when building social networks, recommendation engines, knowledge graphs, or fraud detection. Covers Neo4j (primary), ArangoDB, Amazon Neptune, Cypher query patterns, and graph data modeling.

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。