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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 |
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Workflows
- Workflow:Vllm project Vllm Structured Output Generation
- Workflow:Alibaba ROLL Reward Flow Diffusion Pipeline
- Workflow:Tensorflow Serving Model Version Management
- Workflow:Apache Hudi Docker Demo Setup
- Workflow:Sgl project Sglang Online Serving With OpenAI API
- Workflow:Apache Druid Visual Data Exploration
- Workflow:Ggml org Llama cpp LoRA Adapter Workflow
- Workflow:Evidentlyai Evidently Monitoring Dashboard Setup
- Workflow:Microsoft LoRA LoRA Integration
- Workflow:Ollama Ollama OpenAI API Compatibility
Principles
- Principle:Apache Paimon Blob Descriptor Construction
- Principle:Microsoft Agent framework Conditional Routing
- Principle:Risingwavelabs Risingwave CDC PostgreSQL Configuration
- Principle:FlowiseAI Flowise Evaluation Dataset Creation
- Principle:Shiyu coder Kronos CSV Finetuning Configuration
- Principle:CARLA simulator Carla Navigation Agent Architecture
- Principle:Huggingface Diffusers Video Input Preparation
- Principle:Gretelai Gretel synthetics LSTM Model Building
- Principle:Tencent Ncnn SSD Object Detection
- Principle:Pyro ppl Pyro Funsor Backend HMM
Implementations
- Implementation:Eric mitchell Direct preference optimization Get Batch Logps
- Implementation:TA Lib Ta lib python TA Initialize Shutdown
- Implementation:PacktPublishing LLM Engineers Handbook HuggingFaceProcessor Run
- Implementation:Google deepmind Mujoco GLFW Init CreateWindow
- Implementation:Open compass VLMEvalKit VGRPBench Hitori
- Implementation:ARISE Initiative Robosuite TransportGroup
- Implementation:Openai Openai python Request Transform Utils
- Implementation:Sgl project Sglang Marlin Dequant
- Implementation:Langchain ai Langchain OpenAI Moderation Middleware
- Implementation:Microsoft Onnxruntime CUDA BatchScale
Heuristics
- Heuristic:Kserve Kserve Prefix Cache Consistency
- Heuristic:Spotify Luigi Marker Table Idempotency
- Heuristic:Princeton nlp SimPO Dropout Disabling
- Heuristic:Vespa engine Vespa RPM Zstd Compression Settings
- Heuristic:Microsoft LoRA Scaling Factor Alpha Over R
- Heuristic:BerriAI Litellm Streaming Loop Detection
- Heuristic:Unslothai Unsloth Gradient Accumulation Accuracy
- Heuristic:DistrictDataLabs Yellowbrick Scikit Learn API Compatibility
- Heuristic:Apache Druid Explore Compare Query Strategy
- Heuristic:Openai Evals Chat Format Recommendation
Environments
- Environment:Anthropics Anthropic sdk python Python SDK Core Environment
- Environment:Sgl project Sglang CUDA Runtime
- Environment:Axolotl ai cloud Axolotl Python Runtime
- Environment:Datahub project Datahub Java Build
- Environment:ThreeSR Awesome Inference Time Scaling Python Runtime Environment
- Environment:Neuml Txtai Optional Extras Dependencies
- Environment:NVIDIA DALI FFmpeg Environment
- Environment:Truera Trulens Streamlit Dashboard Environment
- Environment:Bitsandbytes foundation Bitsandbytes CUDA GPU Runtime
- Environment:Testtimescaling Testtimescaling github io GitHub Actions Runner