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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:SeldonIO Seldon core Model Explainability
- Workflow:Datajuicer Data juicer LLM Powered Data Generation
- Workflow:Getgauge Taiko Headless Browser Testing
- Workflow:Speechbrain Speechbrain Speaker Embedding Training
- Workflow:Confident ai Deepeval Synthetic Dataset Generation
- Workflow:OpenGVLab InternVL LoRA Finetuning
- Workflow:Deepspeedai DeepSpeed Pipeline Parallel Training
- Workflow:Lance format Lance Full Text Search
- Workflow:Mlfoundations Open flamingo Distributed Training
- Workflow:Pola rs Polars Time Series Analysis
Principles
- Principle:Puppeteer Puppeteer Browser Context Isolation
- Principle:Huggingface Trl DPO Argument Configuration
- Principle:Facebookresearch Audiocraft Training Checkpoint Resolution
- Principle:Langgenius Dify Input Variable Definition
- Principle:Heibaiying BigData Notes Flink Stream Transformations
- Principle:Dagster io Dagster Software Defined Assets
- Principle:LLMBook zh LLMBook zh github io Pretraining Dataset Preparation
- Principle:Astronomer Astronomer cosmos Watcher Producer Consumer Execution
- Principle:Mlfoundations Open flamingo Distributed Checkpointing
- Principle:Alibaba MNN LLM Runtime Configuration
Implementations
- Implementation:FlagOpen FlagEmbedding VideoLLaVA Open Bench
- Implementation:Ollama Ollama Tokenizer BPE
- Implementation:Microsoft Onnxruntime MapInfo
- Implementation:Alibaba MNN RapidJSON Encodings
- Implementation:Apache Beam InMemoryJobService Prepare
- Implementation:Microsoft Onnxruntime OrtCUDAProviderOptions
- Implementation:Lance format Lance Java Branch
- Implementation:Run llama Llama index RouterRetriever
- Implementation:Alibaba MNN FlexBuffers Header
- Implementation:Apache Paimon GlobalIndexScanBuilder Build
Heuristics
- Heuristic:Sgl project Sglang Chunked Prefill OOM Prevention
- Heuristic:Cleanlab Cleanlab KNN Distance Metric Selection
- Heuristic:SeldonIO Seldon core Tracing Latency Tip
- Heuristic:Openai CLIP CLIP Normalization Constants
- Heuristic:Eric mitchell Direct preference optimization TF32 Matmul Precision
- Heuristic:InternLM Lmdeploy Max Batch Size Selection
- Heuristic:Huggingface Diffusers Guidance Scale Defaults
- Heuristic:ChenghaoMou Text dedup Bloom Filter Single Process
- Heuristic:Mbzuai oryx Awesome LLM Post training Checkpoint Every 3 Papers
- Heuristic:Danijar Dreamerv3 XLA GPU Optimization Flags
Environments
- Environment:Isaac sim IsaacGymEnvs Pip Dependencies
- Environment:PrefectHQ Prefect Prefect Server Database
- Environment:Nightwatchjs Nightwatch BrowserStack Cloud
- Environment:Protectai Llm guard API Server Deployment
- Environment:Treeverse LakeFS Spark GC Environment
- Environment:Ggml org Llama cpp Metal GPU Environment
- Environment:Dotnet Machinelearning TorchSharp Environment
- Environment:LMCache LMCache CUDA GPU Runtime
- Environment:LMCache LMCache Python Runtime
- Environment:Alibaba ROLL SGLang Inference Environment