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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:Onnx Onnx Model Creation
- Workflow:Hpcaitech ColossalAI DPO Alignment
- Workflow:Turboderp org Exllamav2 Multimodal Vision Inference
- Workflow:Googleapis Python genai Function Calling and Tools
- Workflow:Mlc ai Web llm Structured Output Generation
- Workflow:Cleanlab Cleanlab Classification Label Issue Detection
- Workflow:Elevenlabs Elevenlabs python Voice Cloning
- Workflow:Openai Openai python Chat Completion
- Workflow:LLMBook zh LLMBook zh github io Inference and Quantization
- Workflow:MarketSquare Robotframework browser Plugin Development
Principles
- Principle:Ggml org Llama cpp BatchProcessing
- Principle:OpenRLHF OpenRLHF Agent Based Rollout Collection
- Principle:PeterL1n BackgroundMattingV2 Image dataset loading
- Principle:Apache Druid Query Execution
- Principle:Speechbrain Speechbrain Perceptual Quality Evaluation
- Principle:Huggingface Datatrove Tokenized Dataset Loading
- Principle:Google deepmind Mujoco Quasi Random Sequences
- Principle:Microsoft Agent framework Agent Executor Wrapping
- Principle:Puppeteer Puppeteer Platform Detection
- Principle:SeldonIO Seldon core Usage Metrics Publishing
Implementations
- Implementation:Explodinggradients Ragas LangSmith Integration
- Implementation:Recommenders team Recommenders TF Utils
- Implementation:Sgl project Sglang Get Model Loader
- Implementation:Explodinggradients Ragas ResponseRelevancy Metric
- Implementation:BerriAI Litellm Prompt Management Base
- Implementation:Onnx Onnx Checker Cpp API
- Implementation:Sgl project Sglang Sgl Function Decorator
- Implementation:FlowiseAI Flowise SuggestionOption
- Implementation:Openai Openai python Tool Choice MCP
- Implementation:Microsoft DeepSpeedExamples BingBert TuringSources
Heuristics
- Heuristic:Datahub project Datahub Docker Memory Preflight
- Heuristic:NVIDIA NeMo Aligner DPO Sequence Packing Tips
- Heuristic:Apache Paimon Vector Index Configuration Tips
- Heuristic:ARISE Initiative Robomimic BatchNorm To GroupNorm For EMA
- Heuristic:OpenBMB UltraFeedback Score Parsing Robustness
- Heuristic:Neuml Txtai MacOS Stability Workarounds
- Heuristic:Sktime Pytorch forecasting Target Normalization Transforms
- Heuristic:Apache Kafka Log4j Migration Compatibility
- Heuristic:Astronomer Astronomer cosmos Dbt Invocation Mode Selection
- Heuristic:Facebookresearch Audiocraft Audio Normalization Strategies
Environments
- Environment:Dagster io Dagster DAGSTER HOME Configuration
- Environment:Lm sys FastChat LoRA QLoRA Training Environment
- Environment:Huggingface Diffusers Training Environment
- Environment:Tencent Ncnn PyTorch Environment
- Environment:Openai Evals Optional Provider APIs
- Environment:Apache Beam Dataflow Streaming Runtime
- Environment:Huggingface Datatrove Python Runtime
- Environment:Tensorflow Tfjs Node Native Runtime
- Environment:Norrrrrrr lyn WAInjectBench OpenAI API Credentials
- Environment:Marker Inc Korea AutoRAG Korean NLP Dependencies