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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:Groq Groq python Chat Completion
- Workflow:Turboderp org Exllamav2 Text Generation
- Workflow:Online ml River Drift Adaptive Classification
- Workflow:Open compass VLMEvalKit Adding Custom VLM
- Workflow:Spcl Graph of thoughts GoT Sorting Pipeline
- Workflow:Google deepmind Dm control Locomotion Task Setup
- Workflow:Apache Dolphinscheduler Workflow Failover Recovery
- Workflow:Teamcapybara Capybara Selenium Driver Configuration
- Workflow:Heibaiying BigData Notes Storm Topology Development
- Workflow:Openai Openai node Realtime Conversation
Principles
- Principle:LaurentMazare Tch rs TorchScript Export
- Principle:Apache Shardingsphere Metadata Repository Persistence
- Principle:Nightwatchjs Nightwatch Extension Usage In Tests
- Principle:AnswerDotAI RAGatouille In Memory Document Encoding
- Principle:Lucidrains X transformers Iterative Masked Generation
- Principle:LaurentMazare Tch rs Backpropagation Training
- Principle:Lucidrains X transformers Hybrid Discrete Continuous Tokens
- Principle:Google deepmind Dm control Props and Targets
- Principle:ArroyoSystems Arroyo Connection Table Configuration
- Principle:OpenGVLab InternVL Weighted Multi Dataset Training
Implementations
- Implementation:CARLA simulator Carla Vehicle Doors Demo
- Implementation:Bentoml BentoML IO Descriptor NumpyNdarray
- Implementation:Cohere ai Cohere python V2Client Chat Stream
- Implementation:Apache Shardingsphere StatisticsChangedHandler Handle
- Implementation:LLMBook zh LLMBook zh github io Get Data DPO
- Implementation:NVIDIA TransformerEngine JAX Flax Transformer
- Implementation:AUTOMATIC1111 Stable diffusion webui Merged model save and register
- Implementation:Risingwavelabs Risingwave Cargo Workspace Configuration
- Implementation:NVIDIA TransformerEngine Cast Transpose Noop API
- Implementation:Huggingface Datatrove ParquetReader
Heuristics
- Heuristic:Intel Ipex llm Use Cache Training Vs Inference
- Heuristic:Tensorflow Serving Warning Deprecated CreateTfrtSavedModel Raw
- Heuristic:Arize ai Phoenix AIMD Concurrency Control
- Heuristic:Recommenders team Recommenders TensorFlow Session Ordering
- Heuristic:Cypress io Cypress Global Install Warning
- Heuristic:Ucbepic Docetl Rate Limit Exponential Backoff
- Heuristic:Langchain ai Langchain Retry Scope Best Practice
- Heuristic:Mistralai Client python Stream File Uploads
- Heuristic:Online ml River HST Feature Scaling Requirement
- Heuristic:Google deepmind Mujoco Thread Pool Configuration
Environments
- Environment:Dotnet Machinelearning OneDal Acceleration
- Environment:Openai CLIP Python Dependencies
- Environment:Microsoft Onnxruntime Nodejs Runtime Environment
- Environment:FlagOpen FlagEmbedding GPU Accelerator Environment
- Environment:Microsoft DeepSpeedExamples RLHF Training Environment
- Environment:Google research Deduplicate text datasets Rust Cargo Build Environment
- Environment:Protectai Modelscan Python Core Runtime
- Environment:Apache Spark Kubernetes Runtime
- Environment:Testtimescaling Testtimescaling github io GitHub Actions Runner
- Environment:Neuml Txtai Python Core Dependencies