Fine-tuning

FineTuneWarden

Fine-tuning bakes data into models. FineTuneWarden tracks datasets, consent, and eval deltas for every tune.

In the pipeline — products publishing now

The FineTuneWarden store

Stocking up now: a 50-product roadmap is in production and new self-serve kits publish daily — 0 live products today. Start free below while the shelves fill.

How the FineTuneWarden ecosystem runs

Three loops feed each other — content brings readers, readers become buyers, buyers climb the ladder.

📝 Content loop

Fine-tuning explainers, checklists, and teardown playbooks — the Fine-tuning library with no home until now.

🧲 Lead loop

Fine-tuning teams find the content, grab the free playbook, and climb into the FineTuneWarden product line.

🪜 Product loop

$19 starter kits climb to $29 tools and templates, $49 packs and decks, and $149 flagship kits.

Start here

Three free or cheap entry points — pick whichever fits.

1

Free MIT playbook

The ghostcorpnet playbook — free, MIT-licensed. Read it here →

2

The $5 AI Agent Risk Scan

A five-minute self-audit of your agent setup. Get the scan →

3

Browse the catalog

Every ghostcorpnet product in one filterable grid. Open the catalog →

Build on FineTuneWarden

Every ecosystem follows the open ghostcorpnet Pack Standard v1 — interoperable packs, a public directory, and a certification badge.

Stores in FineTuneWarden

50 specialized stores — each one a sub-niche of Fine-tuning. New kits publish daily.

Fine-Tuning Basics Store

Teach models new tricks.

1 in the pipeline

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Data Curation Store

Good data in, good model out.

1 in the pipeline

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Data Provenance Store

Know where data came from.

1 in the pipeline

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De-identification Store

Strip PII before training.

1 in the pipeline

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Data Cards Store

Document every dataset.

1 in the pipeline

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RAG vs Fine-Tuning Store

Choose the right approach.

1 in the pipeline

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LoRA Basics Store

Efficient fine-tuning.

1 in the pipeline

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Eval Before Deploy Store

Prove the tuned model works.

1 in the pipeline

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Hyperparameters Store

Tune the tuning.

1 in the pipeline

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Dataset Formatting Store

Format data models learn from.

1 in the pipeline

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Preference Data Store

Teach models what humans prefer.

1 in the pipeline

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Synthetic Data Store

Generate training data.

1 in the pipeline

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Data Licensing Store

Legal data for training.

1 in the pipeline

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Contamination Control Store

Keep evals clean.

1 in the pipeline

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Catastrophic Forgetting Store

Don't lose old skills.

1 in the pipeline

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Safety Tuning Store

Tune without breaking safety.

1 in the pipeline

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Domain Adaptation Store

Models for your domain.

1 in the pipeline

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Multilingual Tuning Store

Tune across languages.

1 in the pipeline

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Quantized Training Store

Train on less hardware.

1 in the pipeline

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Distributed Training Store

Scale across GPUs.

1 in the pipeline

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Checkpoint Management Store

Never lose a good model.

1 in the pipeline

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Model Merging Store

Combine tuned models.

1 in the pipeline

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Distillation Store

Small models, big knowledge.

1 in the pipeline

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Training Infrastructure Store

Hardware that trains.

1 in the pipeline

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Experiment Tracking Store

Every run, recorded.

1 in the pipeline

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Hyperparameter Search Store

Search systematically.

1 in the pipeline

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Data Versioning Store

Version training data.

1 in the pipeline

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Bias Audits Store

Audit tuned models for bias.

1 in the pipeline

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Regulated Tuning Store

Tune in regulated industries.

1 in the pipeline

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Model Cards Store

Document tuned models.

1 in the pipeline

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IP Strategy Store

Protect tuned models.

1 in the pipeline

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Tuning Marketplaces Store

Buy tuned models.

1 in the pipeline

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Continual Learning Store

Models that keep learning.

1 in the pipeline

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Federated Tuning Store

Tune without centralizing data.

1 in the pipeline

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On-Device Tuning Store

Personalize on the device.

1 in the pipeline

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Tuning for Agents Store

Models built for tool use.

1 in the pipeline

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Reward Modeling Store

Teach models human values.

1 in the pipeline

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Constitutional Tuning Store

Principles into weights.

1 in the pipeline

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Tuning Research Lab Store

Frontier tuning science.

1 in the pipeline

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Tuning Infrastructure Store

Platforms for tuning teams.

1 in the pipeline

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Tuning Certification Store

Certify ML engineers.

1 in the pipeline

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Active Learning Store

Label what matters most.

1 in the pipeline

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Annotation Operations Store

Labeling at scale.

1 in the pipeline

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Curriculum Learning Store

Easy examples first.

1 in the pipeline

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Training Efficiency Store

Faster, cheaper training.

1 in the pipeline

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Early Stopping Store

Stop before overfitting.

1 in the pipeline

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Model Soups Store

Averaging for robustness.

1 in the pipeline

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Tuning Cost Models Store

Budget every experiment.

1 in the pipeline

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The Fine-Tuning Bible Store

The complete reference.

1 in the pipeline

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Enterprise Tuning Program Store

Company-wide tuning strategy.

1 in the pipeline

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Works with

Cluster: Agent Platform

FineTuneWarden runs alongside its cluster siblings and plugs into related ecosystems across the ghostcorpnet constellation.

SourceLattice

Open-source agent stacks

Ship open-source agent stacks with governance baked in, not bolted on.

Explore →

RAGLattice

RAG systems

Retrieval agents that cite their sources.

Explore →

VoiceWarden

Voice agents

Voice agents that sound right — and behave.

Explore →

DataLattice

Data engineering

Pipeline agents with data contracts.

Explore →

SecWarden

AI agent security

Attack your agents before someone else does: injection tests, guardrails, and tamper-evident logs.

Explore →