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How to Use: LM Studio Model Runtime Map from Library Inventory (No Invented Token Counts)

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How to use the LM Studio Model Runtime Map from Library Inventory (No Invented Token Counts) PromptDig prompt without inventing metrics.

How to Use: LM Studio Model Runtime Map from Library Inventory (No Invented Token Counts)

You pasted a messy LM Studio inventory and need a clean deliverable without invented numbers. This PromptDig prompt turns only what you already listed into a structured map or checklist for lm studio model runtime map handoffs.

What this prompt does

It locks your inventory, version, workspace label, and domain fields, then builds a ledger plus a table that refuses fake metrics. Missing cells stay NOT IN INPUTS instead of guessing.

Use it when you already have real stubs from LM Studio and want a teachable map for this job, not a generic template swap from another vendor. The Generate steps name LM Studio nouns on purpose so a title swap into another category would fail the swap-title test.

The deliverable is aimed at LM Studio maps. Reviewers should see Inventory nouns echoed in the table rows, not marketing fluff. Cap style limits stay soft unless you add them later in Extra.

How to fill the brackets

  1. Paste your Inventory with concrete nouns only. Prefer two labeled rows so the example shape stays visible after you swap names.
  2. Lock Version to what you actually run. If you do not know the version, write unknown rather than guessing a marketing release name.
  3. Fill Workspace and SpecNames only when you already have labels you are allowed to quote.
  4. Complete the domain fields that match this job. Leave blanks as UNKNOWN instead of inventing token counts, VRAM totals, or latency scores.
  5. Set Banned and Never to the phrases you refuse. Keep Format and Lang explicit.

Who it is for

Local-llm users who inherit messy lm studio library inventories. It is also useful when a teammate hands you a partial export and you need a map that stays honest about gaps.

How to run it

  1. Open LM Studio Model Runtime Map from Library Inventory (No Invented Token Counts) on PromptDig.
  2. Copy the prompt into ChatGPT, Claude, or Gemini.
  3. Replace every bracket with your locked fields.
  4. Ask for the ledger first if you want a quick honesty check, then the full table.
  5. Compare the output rows to your Inventory. Cut any invented token counts, VRAM totals, or latency scores.

What good output looks like

A strong run opens with an honesty ledger that restates your nouns, then a numbered map with one row per stub. Spec names stay limited to SpecNames. Version lock refuses features you did not name. The refuse list and compliance pass quote Banned and Never hits instead of inventing metrics.

If a cell was blank in Inputs, the model should write NOT IN INPUTS. That is success, not a failure.

Common mistakes

  • Swapping in a Ollama or GPT4All workflow and keeping the same body. The prompt should teach LM Studio language.
  • Asking the model to invent token counts, VRAM totals, or latency scores so the table looks complete. Refuse that and keep gaps visible.
  • Pasting bare URLs without labeled links when you share the result. Prefer clear titles.

Related links

Bottom line

Ship the map your Inventory already supports. Keep LM Studio nouns specific, keep invented metrics out, and leave missing fields marked so the next human can fill them for real.