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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:Run llama Llama index Evaluation Pipeline
- Workflow:Hiyouga LLaMA Factory LoRA SFT Finetuning
- Workflow:Protectai Modelscan CLI Model Scanning
- Workflow:ChenghaoMou Text dedup MinHash LSH Deduplication
- Workflow:Princeton nlp Tree of thought llm ToT BFS experiment
- Workflow:Getgauge Taiko Headless Browser Testing
- Workflow:Protectai Llm guard API Server Deployment
- Workflow:Eventual Inc Daft Multimodal AI Batch Inference
- Workflow:Tensorflow Tfjs GPT2 Text Generation
- Workflow:Googleapis Python genai Multimodal Content Generation
Principles
- Principle:SeldonIO Seldon core Component Model Deployment
- Principle:Apache Airflow Branch Preparation
- Principle:OpenRLHF OpenRLHF Optimizer and Scheduler Setup
- Principle:Microsoft Autogen Hierarchical Agent Composition
- Principle:Microsoft Autogen Graph Execution
- Principle:Sdv dev SDV Multi Table Model Fitting
- Principle:Langchain ai Langchain Release Notes Generation
- Principle:Protectai Llm guard Scanner Configuration Schema
- Principle:Huggingface Trl DPO Training
- Principle:Sktime Pytorch forecasting Samformer Architecture
Implementations
- Implementation:Microsoft Onnxruntime CrossEntropy Declarations
- Implementation:Scikit learn Scikit learn PartialDependenceDisplay
- Implementation:Kubeflow Kubeflow Katib Experiment CRD
- Implementation:Pola rs Polars Collect Streaming Engine
- Implementation:Elevenlabs Elevenlabs python WebhookSignatureVerification
- Implementation:Sktime Pytorch forecasting NHiTS Sub Modules
- Implementation:Openai Openai python Video List Params
- Implementation:Ray project Ray Metric Gauge
- Implementation:Ggml org Llama cpp Debug Header
- Implementation:Microsoft LoRA Legacy Finetune Trainer Seq2Seq
Heuristics
- Heuristic:Apache Shardingsphere Version Cleanup After Switch
- Heuristic:Tencent Ncnn Lightmode Memory Optimization
- Heuristic:Datahub project Datahub Venv Copies Mode
- Heuristic:Princeton nlp SimPO Hyperparameter Tuning
- Heuristic:Hiyouga LLaMA Factory CUDA Memory Optimization
- Heuristic:InternLM Lmdeploy KV Cache Memory Tuning
- Heuristic:Cohere ai Cohere python Embed Auto Batching Strategy
- Heuristic:Langfuse Langfuse LLM Rate Limit 24h Abandon
- Heuristic:Vibrantlabsai Ragas Warning Deprecated Legacy LLM Wrappers
- Heuristic:NVIDIA DALI Memory Pool Tuning
Environments
- Environment:Langfuse Langfuse S3 Compatible Storage
- Environment:Hpcaitech ColossalAI CUDA GPU Environment
- Environment:Rapidsai Cuml Python RAPIDS Stack
- Environment:Interpretml Interpret Python Core Environment
- Environment:Hiyouga LLaMA Factory Optional Inference Backends
- Environment:Microsoft DeepSpeedExamples VisualChat Training Environment
- Environment:Axolotl ai cloud Axolotl Python Runtime
- Environment:LMCache LMCache VLLM Serving Engine
- Environment:Groq Groq python Python Groq SDK
- Environment:Cypress io Cypress Linux Display Server