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train-debug
Interactive diagnostic workflow for training problems. Use when training is failing, loss is stuck, gradients explode, NaN occurs, or convergence is poor.
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tools machine learning AI 技能
发现 tools machine learning 相关 Skills，比较来源仓库和用途，查看适合你工作流的技能说明。
分类目录: tools machine learning
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GitHub
train
Execute a neural network training run with mandatory monitoring and best-practice defaults. Use when user wants to train a model, start training, or run a training job.
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GitHub
run-validation
Run model validation on a dataset. Use when testing model performance, comparing checkpoints, or running final evaluation.
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GitHub
interpret-curves
Analyze training logs and explain what's happening. Use when reviewing training runs, understanding loss curves, or diagnosing completed training.
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GitHub
scaling-analysis
Run scaling experiments to understand model/data/compute relationships. Use when investigating scaling laws, compute-optimal training, or model size decisions.
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GitHub
azure-ai-projects-client-library-skill
Expert guidance for using the Azure AI Projects client library (azure-ai-projects) to build and deploy AI applications with Microsoft Foundry. This skill covers agent creation, tools integration, evaluation, co...
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GitHub
principal-data-engineer
Expert-level guidance on data platform architecture, pipeline design patterns, and engineering rigor. Use this skill when designing new data platforms, reviewing complex DAGs, or establishing engineering standa...
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GitHub
lm-studio
This skill should be used when the user asks to "run local LLMs", "use LM Studio", "configure local AI server", "estimate VRAM requirements", "load a model locally", or needs guidance on OpenAI-compatible local...
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GitHub
hugging-face
This skill should be used when the user asks about "Hugging Face", "HF Hub", "transformers", "model hub", or needs guidance on which Hugging Face capability to use. Acts as an entry-point that routes to special...
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GitHub
memory-write
Persist a decision or learning to Mother-Harness long-term memory
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GitHub
data-analyst
Analyze data, identify trends, and generate visualization recommendations
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GitHub
exps-logistic
Documentation for the logistic regression MI estimation experiment (exps_logistic)
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GitHub
ai-workflow-integration
Convert AI fluency into throughput by embedding AI into repeatable workflows with triggers, quality gates, and iteration loops that compound over time.
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GitHub
ai-system-governance
Scale AI fluency beyond individuals through standards, guardrails, audit trails, and organizational policies that maintain quality and accountability.
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GitHub
ai-system-literacy
Build accurate mental models of AI behavior: understand context windows, probabilistic generation, hallucination causes, and predict failure modes before they occur.
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GitHub
performance-optimizer
Copilot agent that assists with performance analysis, bottleneck detection, optimization strategies, and benchmarking Trigger terms: performance optimization, performance tuning, profiling, benchmark, bottlene...
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GitHub
ai-ml-engineer
Copilot agent that assists with machine learning model development, training, evaluation, deployment, and MLOps Trigger terms: machine learning, ML, AI, model training, MLOps, model deployment, feature enginee...
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GitHub
rlm-patterns
Library of Recursive Language Model analysis patterns. Reference when designing analysis strategies for large documents.
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GitHub
data-orchestrator
Central data strategy coordinator for AI-driven crypto trading. Use when building data pipelines, validating data quality, coordinating multi-source data aggregation, or implementing ML-ready data infrastructur...
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GitHub
time-series-analysis
Temporal pattern detection and forecasting. Use when analyzing trends over time, detecting seasonality, identifying anomalies in time series, or building simple forecasting models.
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GitHub
finetuning
Model fine-tuning with PyTorch and HuggingFace Trainer. Covers dataset preparation, tokenization, training loops, TrainingArguments, SFTTrainer for instruction tuning, evaluation, and checkpoint management. Inc...
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GitHub
dpo
Direct Preference Optimization for learning from preference pairs. Covers DPOTrainer, preference dataset preparation, implicit reward modeling, and beta tuning for stable preference learning without explicit re...
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GitHub
rloo
Reinforcement Learning with Leave-One-Out estimation for policy optimization. Covers RLOOTrainer, reward function integration, baseline estimation, and variance reduction techniques for stable RL training. Incl...
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GitHub
localai
LocalAI local inference API management via Podman Quadlet. Provides an OpenAI-compatible API for local model inference with GPU acceleration. Use when users need to configure, start, or manage the LocalAI servi...
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默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库，同一仓库的多个技能可能共享相同数值；它反映仓库关注度，不代表单个技能的安装量或质量评分。