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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:Microsoft Playwright Codegen test recording
- Workflow:Lucidrains X transformers Non Autoregressive Masked Generation
- Workflow:MarketSquare Robotframework browser Browser Test Authoring
- Workflow:Mlc ai Mlc llm Python Engine Inference
- Workflow:Princeton nlp Tree of thought llm ToT BFS experiment
- Workflow:Openclaw Openclaw Agent Message Loop
- Workflow:Promptfoo Promptfoo Red Team Security Scan
- Workflow:Pytorch Serve Model Deployment
- Workflow:Guardrails ai Guardrails LLM Output Validation
- Workflow:Ggml org Llama cpp Model Perplexity Evaluation
Principles
- Principle:Sgl project Sglang Frontend Backend Initialization
- Principle:Openai Evals Result Aggregation
- Principle:Ggml org Llama cpp Sampling System
- Principle:Huggingface Transformers Adapter Loading And Switching
- Principle:Huggingface Diffusers Selective Test Execution
- Principle:Langgenius Dify Service Layer Architecture
- Principle:Bitsandbytes foundation Bitsandbytes HPU 4bit Dequantization
- Principle:Apache Flink Object Reuse
- Principle:Huggingface Datatrove Contamination Statistics
- Principle:Apache Spark Test Orchestration
Implementations
- Implementation:Microsoft Onnxruntime CUDA NcclService
- Implementation:Tencent Ncnn Onnx2ncnn
- Implementation:InternLM Lmdeploy GptKernels
- Implementation:Ray project Ray Ray Shutdown
- Implementation:SeleniumHQ Selenium Git Fork And Branch Pattern
- Implementation:Run llama Llama index Download Module
- Implementation:Kubeflow Pipelines XGBoost Predict On CSV Op
- Implementation:Huggingface Transformers Setup Py
- Implementation:Datajuicer Data juicer PythonFileMapper
- Implementation:EvolvingLMMs Lab Lmms eval MathVision Eval Utils
Heuristics
- Heuristic:Puppeteer Puppeteer Chrome Default Launch Arguments
- Heuristic:Kserve Kserve Autoscaler Concurrency Target
- Heuristic:Apache Beam Lock Contention Batching
- Heuristic:Fede1024 Rust rdkafka Manual Offset Store Pattern
- Heuristic:ARISE Initiative Robosuite Numba BSOD Workaround
- Heuristic:Gretelai Gretel synthetics GPU Memory Allow Growth
- Heuristic:Microsoft Onnxruntime Threading Configuration Tips
- Heuristic:Dotnet Machinelearning Sparsity Threshold Optimization
- Heuristic:Snorkel team Snorkel NLP Preprocessor Memoization
- Heuristic:Mbzuai oryx Awesome LLM Post training Depth Limit Recursion At 2
Environments
- Environment:ContextualAI HALOs CUDA 12 1 Training Environment
- Environment:Deepspeedai DeepSpeed NVMe Environment
- Environment:Haifengl Smile Java 25 Runtime
- Environment:Astronomer Astronomer cosmos Kubernetes Provider
- Environment:Vllm project Vllm Python
- Environment:Kserve Kserve VLLM Runtime
- Environment:CrewAIInc CrewAI Python Runtime Environment
- Environment:Huggingface Alignment handbook Evaluation Tools
- Environment:NVIDIA TransformerEngine Python PyTorch Requirements
- Environment:Mit han lab Llm awq Python Runtime Environment