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1,118
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:Heibaiying BigData Notes Storm Topology Development
- Workflow:Risingwavelabs Risingwave Iceberg Lakehouse Ingestion
- Workflow:ContextualAI HALOs Model Evaluation
- Workflow:Lm sys FastChat Vicuna SFT Finetuning
- Workflow:Turboderp org Exllamav2 Interactive Chat
- Workflow:Vllm project Vllm Multi LoRA Serving
- Workflow:Openai Whisper Word Level Timestamps
- Workflow:Neuml Txtai Semantic Search Pipeline
- Workflow:ThreeSR Awesome Inference Time Scaling Automated Paper Addition
- Workflow:Microsoft Semantic kernel Plugin Integration And Function Calling
Principles
- Principle:PacktPublishing LLM Engineers Handbook Query Expansion
- Principle:Online ml River Holt Winters Forecasting
- Principle:Online ml River Online Pattern Adaptation
- Principle:Mlflow Mlflow Code Instrumentation
- Principle:Intel Ipex llm Data Preparation For Finetuning
- Principle:Webdriverio Webdriverio Cloud Session Management
- Principle:Mlc ai Mlc llm Orchestrated Deployment Launch
- Principle:Evidentlyai Evidently Monitoring UI Launch
- Principle:Kubeflow Pipelines Incremental Model Training
- Principle:Iamhankai Forest of Thought Chain of Thought Reasoning
Implementations
- Implementation:Alibaba MNN RapidJSON Writer
- Implementation:Datajuicer Data juicer WordRepetitionFilter
- Implementation:Guardrails ai Guardrails ValidationOutcome Stream
- Implementation:Haifengl Smile Chromosome
- Implementation:Anthropics Anthropic sdk python Messages Create With Thinking
- Implementation:Ggml org Ggml Gpt tokenize
- Implementation:Infiniflow Ragflow Agent Hooks
- Implementation:Zai org CogVideo SAT Get Args
- Implementation:Recommenders team Recommenders TfidfRecommender
- Implementation:Googleapis Python genai Interactions Resource
Heuristics
- Heuristic:LaurentMazare Tch rs CuDNN Benchmark Mode
- Heuristic:MaterializeInc Materialize CI Retry Strategies
- Heuristic:Alibaba ROLL GPU Memory Offload Strategy
- Heuristic:Openclaw Openclaw Retry With Exponential Backoff
- Heuristic:Bentoml BentoML Warning Deprecated Server Module
- Heuristic:Helicone Helicone ClickHouse ReplacingMergeTree FINAL
- Heuristic:CrewAIInc CrewAI Rate Limiting Strategy
- Heuristic:Junyanz Pytorch CycleGAN and pix2pix Identity Loss Color Preservation
- Heuristic:Sktime Pytorch forecasting Gradient Clipping Value
- Heuristic:SqueezeAILab ETS Softmax Temperature Tuning
Environments
- Environment:Haifengl Smile Native BLAS LAPACK ARPACK
- Environment:Mbzuai oryx Awesome LLM Post training Python Pandas
- Environment:Ggml org Ggml C Cpp Build Environment
- Environment:Sgl project Sglang Kubernetes
- Environment:DevExpress Testcafe Firefox Marionette
- Environment:Microsoft Autogen Python Runtime Environment
- Environment:Lm sys FastChat SFT Training Environment
- Environment:Mit han lab Llm awq CUDA Build Environment
- Environment:Vllm project Vllm CUDA GPU Runtime
- Environment:Neuml Txtai Python Core Dependencies