Module experiment 

Experiment Tracking Integration Module

Integrates with Entrenar Experiment Tracking Spec v1.8.0 for orchestrating ML experiment workflows with full traceability, cost optimization, and academic research support.

Entrenar CLI (v0.2.4)

The entrenar crate provides a comprehensive CLI:

# Training (YAML Mode v1.0)
entrenar train config.yaml           # Train from declarative YAML
entrenar validate config.yaml        # Validate configuration
entrenar init --template lora        # Generate config template

# Model Operations
entrenar quantize model.safetensors --bits 4
entrenar merge model1.st model2.st --method ties

# Research Workflows
entrenar research init --id my-dataset
entrenar research cite artifact.yaml --format bibtex

# Inspection & Auditing
entrenar inspect model.safetensors   # Model/data inspection
entrenar audit data.parquet --type bias
entrenar monitor data.parquet        # Drift detection

# Benchmarking (entrenar-bench)
entrenar-bench temperature --start 1.0 --end 8.0
entrenar-bench cost-performance --gpu a100-80gb

MCP Tooling (pmcp v2.3)

The stack uses PAIML’s pmcp SDK (github.com/paiml/rust-mcp-sdk) for both Model Context Protocol client and server roles — full TypeScript SDK parity covering JSON-RPC framing, stdio/SSE/WebSocket transports, tool registration, and session lifecycle.

Features

• ComputeDevice abstraction (CPU/GPU/TPU/AppleSilicon)
• EnergyMetrics and CostMetrics for efficiency tracking
• ModelParadigm classification
• CostPerformanceBenchmark with Pareto frontier analysis
• SovereignDistribution for air-gapped deployments
• ResearchArtifact with ORCID/CRediT academic support
• CitationMetadata for BibTeX/CFF generation
• Experiment tree visualization for run comparison (MLflow replacement)
• YAML Mode Training v1.0 declarative configuration

Re-exports

pub use types::AppleChip;

pub use types::ComputeDevice;

pub use types::ComputeIntensity;

pub use types::CpuArchitecture;

pub use types::ExperimentError;

pub use types::GpuVendor;

pub use types::ModelParadigm;

pub use types::PlatformEfficiency;

pub use types::TpuVersion;

pub use metrics::CostMetrics;

pub use metrics::EnergyMetrics;

pub use benchmark::CostPerformanceBenchmark;

pub use benchmark::CostPerformancePoint;

pub use research::CitationMetadata;

pub use research::CitationType;

pub use research::CreditRole;

pub use research::Orcid;

pub use research::PreRegistration;

pub use research::ResearchArtifact;

pub use research::ResearchContributor;

pub use run::ExperimentRun;

pub use run::ExperimentStorage;

pub use run::InMemoryExperimentStorage;

pub use run::RunStatus;

pub use sovereign::ArtifactSignature;

pub use sovereign::ArtifactType;

pub use sovereign::OfflineRegistryConfig;

pub use sovereign::SignatureAlgorithm;

pub use sovereign::SovereignArtifact;

pub use sovereign::SovereignDistribution;

Modules

benchmark

Cost-performance benchmarking with Pareto frontier analysis.

metrics

Energy and cost metrics for experiment tracking.

research

Academic research support with ORCID, CRediT, and citation generation.

run

Experiment run tracking and storage.

sovereign

Sovereign distribution manifest for air-gapped deployments

tree

Experiment Tracking Frameworks Tree Visualization

types

Core type definitions for experiment tracking.