---
type: concept
x-llmwiki:
  schemaVersion: "0.1"
  contentHash: a092c5053a2acd664564ed6c549c8a24fdd1bed59df841745c707ed7e6ec0a4c
  pageDirectory: concepts
  sources:
    - applicable-model-terms-databricks-on-aws.md
  confidence: 0.3
  provenanceState: inferred
  freshnessStatus: unverified
  aliases:
    - acceptable-use-policy-for-ml-models
    - AUPFMM
  citations:
    - file: applicable-model-terms-databricks-on-aws.md
title: Acceptable Use Policy for ML Models
description: Policies and terms governing which types of machine learning models are permissible for deployment on Databricks Model Serving.
tags:
  - governance
  - policy
  - machine-learning
timestamp: "2026-06-19T22:07:29.466Z"
---

# Acceptable Use Policy for ML Models

The source material provided for the **Acceptable Use Policy for ML Models** consists only of YAML front matter with a title and URL reference; no substantive policy text is included. As a result, no facts about the policy content can be extracted or summarized from the provided source. ^[applicable-model-terms-databricks-on-aws.md]

The URL referenced in the source (`https://docs.databricks.com/aws/en/machine-learning/model-serving/acceptable-use-models`) suggests that the policy is part of Databricks model serving documentation. However, the full document body was not supplied. ^[applicable-model-terms-databricks-on-aws.md]

## Possible Related Concepts

- [Model Serving](/concepts/model-serving.md) — The infrastructure where acceptable use policies typically apply.
- [Databricks on AWS](/concepts/databricks-on-aws.md) — The platform context for this policy.
- Responsible AI — Broader governance framework that may encompass acceptable use.
- [MLflow Model Registry](/concepts/mlflow-model-registry.md) — Where model terms and governance metadata are managed.

## Sources

- applicable-model-terms-databricks-on-aws.md

# Citations

1. [applicable-model-terms-databricks-on-aws.md](/references/applicable-model-terms-databricks-on-aws-2e13c689.md)
