Main Page
Welcome to Leeroopedia
Your ML & Data Knowledge Wiki. Best practices and expert-level knowledge for Machine Learning and Data Engineering, covering 1000+ frameworks and libraries from training to deployment.
Browse implementation patterns, configuration guides, debugging heuristics, and battle-tested defaults for frameworks like vLLM, DeepSpeed, Megatron-LM, FlashAttention, Triton, Unsloth, LangChain, and many more. Every page is structured so both humans and AI agents can find what they need fast.
Connect your AI coding agent. Plug Leeroopedia into your favorite coding agent, and let it build robust AI/ML systems autonomously:
- SuperML plugin — converts your AI coding agent into an expert ML engineer with agentic memory
- Leeroopedia MCP — search over best-practices and skills of ML/AI
- Kapso — experimentation platform for autonomous AI/ML software building
Browse by Category
| Category | Description | Browse |
|---|---|---|
| Workflows | Step-by-step processes and procedures | Browse All |
| Principles | Core ideas and foundational knowledge | Browse All |
| Implementations | Code-level details and modules | Browse All |
| Heuristics | Best practices and guidelines | Browse All |
| Environments | Setup and configuration guides | Browse All |
Explore Pages
Workflows
- Workflow:Axolotl ai cloud Axolotl Full Finetuning Distributed
- Workflow:CARLA simulator Carla Simulation Setup and First Steps
- Workflow:Apache Hudi Flink Streaming Write
- Workflow:Snorkel team Snorkel Slice Aware Training
- Workflow:Microsoft Semantic kernel Process Orchestration
- Workflow:Hiyouga LLaMA Factory LoRA SFT Finetuning
- Workflow:Openai Openai python Responses API Text Generation
- Workflow:Openclaw Openclaw Multi Agent Routing
- Workflow:Arize ai Phoenix LLM Evaluation Pipeline
- Workflow:Alibaba MNN LLM Deployment Pipeline
Principles
- Principle:Huggingface Datasets Data Download and Preparation
- Principle:Huggingface Trl SFT Dataset Preparation
- Principle:Apache Spark Streaming Lifecycle Management
- Principle:Getgauge Taiko Gauge Test Execution
- Principle:Ray project Ray Cross Language Task Submission
- Principle:Openclaw Openclaw Documentation Site Configuration
- Principle:Vllm project Vllm LLM Engine Initialization
- Principle:Apache Dolphinscheduler Workflow DAG Definition
- Principle:ArroyoSystems Arroyo Pipeline Submission
- Principle:Volcengine Verl SFT Data Preparation
Implementations
- Implementation:Ggml org Llama cpp Memory Hybrid ISWA
- Implementation:LMCache LMCache Config Base
- Implementation:MaterializeInc Materialize Service Init
- Implementation:Open compass VLMEvalKit VisualGLM
- Implementation:ArroyoSystems Arroyo State Tables
- Implementation:Puppeteer Puppeteer Puppeteer Class
- Implementation:Ollama Ollama Convert Llama Adapter
- Implementation:FlowiseAI Flowise RateLimit
- Implementation:NVIDIA DALI C API Legacy
- Implementation:ARISE Initiative Robosuite HumanoidModel
Heuristics
- Heuristic:Openai Openai node Warning Deprecated Assistants API
- Heuristic:Predibase Lorax GPU Sampling Optimization
- Heuristic:BerriAI Litellm Connection Pooling Memory Management
- Heuristic:Mlc ai Web llm Multi Round KV Cache Reuse
- Heuristic:Bigscience workshop Petals Randomized Rebalancing Intervals
- Heuristic:Triton inference server Server Concurrency Throughput Rule
- Heuristic:Tencent Ncnn Lightmode Memory Optimization
- Heuristic:Iterative Dvc Shell Execution Pitfalls
- Heuristic:Zai org CogVideo LoRA Configuration Tips
- Heuristic:Explodinggradients Ragas Failed Metrics Return NaN
Environments
- Environment:Arize ai Phoenix OpenTelemetry SDK
- Environment:Lance format Lance Rust Toolchain
- Environment:Open compass VLMEvalKit Data Storage Environment
- Environment:CrewAIInc CrewAI LLM Provider Credentials
- Environment:Huggingface Datasets PyTorch Integration
- Environment:NVIDIA NeMo Aligner TensorRT LLM Acceleration Environment
- Environment:FlagOpen FlagEmbedding Python PyTorch Environment
- Environment:Microsoft LoRA NLG Eval External Tools
- Environment:Mit han lab Llm awq Flash Attention Environment
- Environment:Sgl project Sglang CUDA Runtime