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Workflows
7,697
Principles
16,832
Implementations
1,245
Heuristics
909
Environments
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.
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| 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:Guardrails ai Guardrails Server Deployment
- Workflow:Sdv dev SDV Data quality evaluation
- Workflow:EvolvingLMMs Lab Lmms eval Server Mode Evaluation
- Workflow:Scikit learn Scikit learn Ensemble Model Building
- Workflow:Lance format Lance Table Optimization
- Workflow:OWASP Www project top 10 for large language model applications Vulnerability Entry Development
- Workflow:Getgauge Taiko Headless Browser Testing
- Workflow:SeldonIO Seldon core Production Monitoring Pipeline
- Workflow:Vllm project Vllm OpenAI Compatible Serving
- Workflow:Tencent Ncnn Post Training Quantization
Principles
- Principle:Apache Paimon Blob Descriptor Construction
- Principle:Turboderp org Exllamav2 Layer Quantization
- Principle:Apache Spark Programmatic Application Launch
- Principle:Sgl project Sglang Multimodal Prompt Construction
- Principle:Datajuicer Data juicer Data Aggregation
- Principle:Deepset ai Haystack Embedding Based Retrieval
- Principle:FlagOpen FlagEmbedding Evaluation Configuration
- Principle:Lm sys FastChat Causal LM Loading
- Principle:Microsoft LoRA Distributed LoRA Training
- Principle:Ollama Ollama CLIDisplay
Implementations
- Implementation:CARLA simulator Carla DebugShape
- Implementation:CrewAIInc CrewAI Code Docs Search Tool
- Implementation:Haosulab ManiSkill PDJointVelController
- Implementation:Triton inference server Server Ensemble Infer Request
- Implementation:Togethercomputer Together python Audio Speech Types
- Implementation:Datahub project Datahub Filter Tag Indexes
- Implementation:Open compass VLMEvalKit PhyX Utils
- Implementation:Apache Paimon VectorSearch Construction
- Implementation:Microsoft Agent framework Content To Function Approval Response
- Implementation:BerriAI Litellm Secret Manager Main
Heuristics
- Heuristic:Vibrantlabsai Ragas Reasoning Model Parameter Constraints
- Heuristic:Mlc ai Web llm Service Worker Keep Alive
- Heuristic:Googleapis Python genai API Retry Backoff Strategy
- Heuristic:Guardrails ai Guardrails Async Vs Sync Validation Mode
- Heuristic:Langchain ai Langchain Error Context Preservation
- Heuristic:DistrictDataLabs Yellowbrick Model Fitted State Detection
- Heuristic:SqueezeAILab ETS Embedding Model GPU Collocation
- Heuristic:NVIDIA DALI Memory Pool Tuning
- Heuristic:Danijar Dreamerv3 Replay Context Carry Init
- Heuristic:NVIDIA NeMo Curator Semantic Dedup Cluster Sizing
Environments
- Environment:Mistralai Client python Realtime Transcription Environment
- Environment:Recommenders team Recommenders Spark Environment
- Environment:MaterializeInc Materialize Kubernetes Helm Runtime
- Environment:Apache Spark Python Environment
- Environment:SqueezeAILab ETS Multi GPU Sglang Runtime
- Environment:Openai Openai agents python OpenAI API Credentials
- Environment:Microsoft DeepSpeedExamples RLHF Training Environment
- Environment:Axolotl ai cloud Axolotl Python Runtime
- Environment:Kserve Kserve Kubernetes Cluster
- Environment:Spcl Graph of thoughts Local LLaMA GPU Inference