Corso · 7 capitoli
Fine-Tuning & Distilling Open Models
From we should fine-tune to a governed loop: LoRA on open weights, distillation from frontier models, and the evals that prove it worked.
Cosa saprai fare
- Six chapters that take an open-weight checkpoint from a fine-tuning decision to a served adapter with a rollback plan.
- A decision tree for when fine-tuning earns its cost, and the lab you'll use to prove it on your own task.
- Turning a pile of scraped examples into the few hundred curated, deduplicated, and licensed rows actually worth training on.
- Sizing the adapter to the task, sizing the GPU to the adapter, and picking the checkpoint that actually generalizes.
- Turning a frontier model's judgment into training signal for your open model, without crossing the line its terms of service draws.
- Turning a single passing score into a documented before/after harness, a capability drift set, and a ship/no-ship gate anyone else could rerun.
Cosa contiene
- 1Fine-Tuning Open Models: Start Here
Six chapters that take an open-weight checkpoint from a fine-tuning decision to a served adapter with a rollback plan.
- 2The Fine-Tuning Decision
A decision tree for when fine-tuning earns its cost, and the lab you'll use to prove it on your own task.
- 3Dataset Engineering for Tuning
Turning a pile of scraped examples into the few hundred curated, deduplicated, and licensed rows actually worth training on.
- 4LoRA & QLoRA in Practice
Sizing the adapter to the task, sizing the GPU to the adapter, and picking the checkpoint that actually generalizes.
- 5Distillation from Frontier Models
Turning a frontier model's judgment into training signal for your open model, without crossing the line its terms of service draws.
- 6Evals That Prove It Worked
Turning a single passing score into a documented before/after harness, a capability drift set, and a ship/no-ship gate anyone else could rerun.
- 7Serving Your Tuned Model
Turning a checkpoint that passed the gate into a live adapter with a name, a canary, and a rollback plan.
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