Understand previous pcrm-model cleanup before a new job
This guide explains that why module-owned fine-tuned models may be deleted when training starts. The guide then takes you through the correct route, the checks to complete before making changes, the workflow in order, and the evidence to review afterwards.
Where to goCode-backed reference → OpenAiProvider::createFineTuningJob
Before you start
- Use an account with Settings: Edit and confirm the intended record or setting before making a change.
- Follow the exact route above. If the screen or action is absent, check module activation, ownership and permissions rather than using another person’s account.
- Use controlled test data for configuration, integration, email, AI, payment, portal or automation changes before production-wide use.
What you’ll accomplish
Know why module-owned fine-tuned models may be deleted when training starts. The instructions reflect the supplied module’s registered menus, controller actions, views, settings and code-backed validation flow.
Follow these steps
- Go to Code-backed reference → OpenAiProvider::createFineTuningJob.
- Select the relevant record, filter, report, model or configuration described below.
- Use the displayed action or read the current values without altering unrelated data.
- Compare the output with the code-backed rules and expected result in this guide.
- Record or correct any mismatch before relying on the output in production.
Fields and options to review
ActionUnderstand previous pcrm-model cleanup before a new job
Exact navigationCode-backed reference → OpenAiProvider::createFineTuningJob
Module version1.0.0
VerificationVerify the saved record, status, output or setting in the same workspace and review any linked activity, file or notification.
Rules the system enforces
- deletePreviousFineTunedModel runs before formatting/upload.
- Only module-owned model IDs identified by the pcrm naming rule are targeted.
How to confirm it worked
- The supported understand previous pcrm-model cleanup before a new job flow completes without bypassing permission or validation checks.
- The resulting record, setting, status, file, delivery event or external response is visible from the relevant workspace.
- Unexpected validation, provider or linked-record errors are investigated before retrying.
Security, privacy and operational checks
- Restrict the API key and AI settings to authorised administrators.
- Do not submit confidential, special-category or unnecessary personal data to the external AI provider.
- Check generated text before using it in customer, staff, legal, financial or compliance communication.
- Monitor provider billing and retention independently because this module has no built-in cost dashboard.
Continue with related guidance
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