GitHub
flow-nexus-neural
Train and deploy neural networks in distributed E2B sandboxes with Flow Nexus
☆ 272查看技能
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
prompt-optimizer
Prompt engineering expert that helps users craft optimized prompts using 57 proven frameworks. Use when users want to optimize prompts, improve AI instructions, create better prompts for specific tasks, or need...
☆ 272查看技能
GitHub
minimax-usage
Monitor Minimax Coding Plan usage to stay within API limits. Fetches current usage stats and provides status alerts.
☆ 230查看技能
GitHub
pi-orchestration
Orchestrate multiple AI models (GLM, MiniMax, etc.) as workers using Pi Coding Agent with Claude as coordinator.
☆ 229查看技能
GitHub
multi-model-validation
Run multiple AI models in parallel for 3-5x speedup with ENFORCED performance statistics tracking. Use when validating with Grok, Gemini, GPT-5, DeepSeek, MiniMax, Kimi, GLM, or Claudish proxy for code review,...
☆ 224查看技能
GitHub
openrouter-trending-models
Fetch trending programming models from OpenRouter rankings. Use when selecting models for multi-model review, updating model recommendations, or researching current AI coding trends. Provides model IDs, context...
☆ 224查看技能
GitHub
proxy-mode-reference
Reference guide for using PROXY_MODE with external AI models. Use when running multi-model reviews, understanding which agents support PROXY_MODE, or debugging external model integration issues. Includes routin...
☆ 224查看技能
GitHub
model-tracking-protocol
MANDATORY tracking protocol for multi-model validation. Creates structured tracking tables BEFORE launching models, tracks progress during execution, and ensures complete results presentation. Use when running...
☆ 224查看技能
GitHub
coot-model-building
Best Practices for Model-Building Tools and Refinement
☆ 154查看技能
GitHub
regression-analysis-modeling
Perform comprehensive regression analysis and predictive modeling using linear regression, decision trees, and random forests. Use when you need to predict continuous values like housing prices, sales forecasts...
☆ 152查看技能
GitHub
mlflow-evaluation
MLflow 3 GenAI evaluation for agent development. Use when (1) writing mlflow.genai.evaluate() code, (2) creating @scorer functions, (3) building evaluation datasets from traces, (4) using built-in scorers (Guid...
☆ 146查看技能
GitHub
tinker-training-cost
Calculate training costs for Tinker fine-tuning jobs. Use when estimating costs for Tinker LLM training, counting tokens in datasets, or comparing Tinker model training prices. Tokenizes datasets using the corr...
☆ 141查看技能
GitHub
tinker
Fine-tune LLMs using the Tinker API. Covers supervised fine-tuning, reinforcement learning, LoRA training, vision-language models, and both high-level Cookbook patterns and low-level API usage.
☆ 141查看技能
GitHub
training-data-curation
Guidelines for creating high-quality datasets for LLM post-training (SFT/DPO/RLHF). Use when preparing data for fine-tuning, evaluating data quality, or designing data collection strategies.
☆ 141查看技能
GitHub
ml-rigor
Enforces baseline comparisons, cross-validation, interpretation, and leakage prevention for ML pipelines
☆ 141查看技能
GitHub
ml-rigor
Enforces baseline comparisons, cross-validation, interpretation, and leakage prevention for ML pipelines
☆ 141查看技能
GitHub
prompt-engineering-patterns
Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production. Use when optimizing prompts, improving LLM outputs, or designing production prompt temp...
☆ 129查看技能
GitHub
llm-evaluation
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or establishing...
☆ 129查看技能
GitHub
ml-pipeline-workflow
Build end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment. Use when creating ML pipelines, implementing MLOps practices, or automating model training a...
☆ 129查看技能
GitHub
ml-training-debugger
Diagnose machine learning training failures including loss divergence, mode collapse, gradient issues, architecture problems, and optimization failures. This skill spawns a specialist ML debugging ...
☆ 124查看技能
GitHub
logprob-prefill-analysis
Reproduces the full prefill sensitivity analysis pipeline for reward hacking indicators. Use when evaluating how susceptible model checkpoints are to exploit-eliciting prefills, computing token-based trajectori...
☆ 124查看技能
GitHub
learn-off
Disable continuous learning mode
☆ 124查看技能
GitHub
prompt-optimization
Expert prompt optimization for LLMs and AI systems. Use when building AI features, improving agent performance, crafting system prompts, or optimizing LLM interactions. Masters prompt patterns and techniques.
☆ 124查看技能
GitHub
cascade-orchestrator
Creates sophisticated workflow cascades coordinating multiple micro-skills with sequential pipelines, parallel execution, conditional branching, and Codex sandbox iteration. Enhanced with multi-model routing (G...
☆ 124查看技能
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。