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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:Volcengine Verl Supervised Fine Tuning
- Workflow:Mlc ai Mlc llm Model Compilation
- Workflow:BerriAI Litellm Response Caching
- Workflow:Fede1024 Rust rdkafka Mock Cluster Testing
- Workflow:Vllm project Vllm Offline Text Generation
- Workflow:Nightwatchjs Nightwatch Component Testing
- Workflow:NVIDIA DALI Object Detection Training TensorFlow
- Workflow:Norrrrrrr lyn WAInjectBench Text Prompt Injection Detection
- Workflow:Langfuse Langfuse Trace ingestion pipeline
- Workflow:Unstructured IO Unstructured Chunking And Embedding
Principles
- Principle:Bitsandbytes foundation Bitsandbytes 4bit Dequantization And Matmul
- Principle:ARISE Initiative Robosuite USD Scene Export
- Principle:Langchain ai Langgraph Edge Configuration
- Principle:OpenRLHF OpenRLHF Iterative DPO
- Principle:Predibase Lorax Chat Adapter Routing
- Principle:Lance format Lance Vector Index Building
- Principle:CARLA simulator Carla Python API Build
- Principle:Ray project Ray Object Store Retrieval
- Principle:Apache Spark Cluster Lifecycle Shutdown
- Principle:Sgl project Sglang Sampling Parameters Preparation
Implementations
- Implementation:MaterializeInc Materialize Composition Up Override
- Implementation:DistrictDataLabs Yellowbrick Anscombe Plot
- Implementation:Vibrantlabsai Ragas DynamicFewShotPrompt
- Implementation:Datajuicer Data juicer Quality Classifier Utils
- Implementation:Alibaba ROLL RewardFL ActorWorker Train Step
- Implementation:Online ml River Stream Iter Arff
- Implementation:Microsoft Onnxruntime CUDA TrainingConcat
- Implementation:OpenRLHF OpenRLHF NemoGym AgentExecutor
- Implementation:Mit han lab Llm awq QuantSiglipEncoder
- Implementation:Google deepmind Mujoco MJWarp Init
Heuristics
- Heuristic:LLMBook zh LLMBook zh github io BF16 Mixed Precision Default
- Heuristic:Anthropics Anthropic sdk python Streaming For Long Requests
- Heuristic:Rapidsai Cuml Dask Data Partitioning
- Heuristic:Openai Evals Chat Format Recommendation
- Heuristic:ARISE Initiative Robosuite Numba BSOD Workaround
- Heuristic:Facebookresearch Audiocraft Codebook Dead Code Expiration
- Heuristic:Turboderp org Exllamav2 Attention Backend Selection
- Heuristic:Vllm project Vllm GPU Memory Utilization Tuning
- Heuristic:Bigscience workshop Petals Short Inference Pool Merging
- Heuristic:Huggingface Transformers Dataloader Pin Memory NonBlocking
Environments
- Environment:Togethercomputer Together python Fine Tuning Data Requirements
- Environment:Microsoft Playwright Browser Binaries Environment
- Environment:NVIDIA DALI CMake Build Environment
- Environment:Kserve Kserve Knative Serving
- Environment:Wandb Weave Trace Server Infrastructure
- Environment:Huggingface Transformers BitsAndBytes Quantization Env
- Environment:Eventual Inc Daft Cloud Storage Credentials
- Environment:Farama Foundation Gymnasium Video Recording Dependencies
- Environment:Arize ai Phoenix Phoenix Server Runtime
- Environment:Recommenders team Recommenders Spark Environment