What infrastructure do we need for fine-tuning?
Fine-tuning turns good models into great ones for you.
How It Works:
Set up GPU/TPU instances, data pipelines for batching, and version control for checkpoints-then run training with monitored learning rates and regular validation.
Key Benefits:
- Controlled environment: Reproducible experiments.
- Cost predictability: Estimate GPU-hours before you start.
- Easy rollback: Resume or revert to previous checkpoints.
Real-World Use Cases:
- Chat customization: Tailor responses to brand voice.
- Fraud detection: Fine-tune on your historical fraud data.
FAQs
Which framework to choose?
How manage versions?
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