models_metadata.md

February 4, 2026 ยท View on GitHub

A full model is composed of 3 types of entities:

  1. The model
  2. The variations
  3. The variation versions

Let's take the example of efficientnet to explain these entities.

A model like efficientnet contains multiple variations.

A variation is a specific variation of the model (e.g. B0, B1, ...) with a certain framework (e.g. TensorFlow2).

Model

To create a model, a special model-metadata.json file must be specified.

Here's a basic example for model-metadata.json:

{
  "ownerSlug": "INSERT_OWNER_SLUG_HERE",
  "title": "INSERT_TITLE_HERE",
  "slug": "INSERT_SLUG_HERE",
  "subtitle": "",
  "isPrivate": true,
  "description": "Model Card Markdown, see below",
  "publishTime": "",
  "provenanceSources": ""
}

You can also use the API command kaggle models init -p /path/to/model to have the API create this file for you for a new model. If you wish to get the metadata for an existing model, you can use kaggle models get username/model-slug.

Contents

We currently support the following metadata fields for models.

  • ownerSlug: the slug of the user or organization
  • title: the model's title
  • slug: the model's slug (unique per owner)
  • licenseName: the name of the license (see the list below)
  • subtitle: the model's subtitle
  • isPrivate: whether or not the model should be private (only visible by the owners). If not specified, will be true
  • description: the model's card in markdown syntax (see the template below)
  • publishTime: the original publishing time of the model
  • provenanceSources: the provenance of the model

Model Variation

To create a model variation, a special model-instance-metadata.json file must be specified.

Here's a basic example for model-instance-metadata.json:

{
  "ownerSlug": "INSERT_OWNER_SLUG_HERE",
  "modelSlug": "INSERT_EXISTING_MODEL_SLUG_HERE",
  "instanceSlug": "INSERT_INSTANCE_SLUG_HERE",
  "framework": "INSERT_FRAMEWORK_HERE",
  "overview": "",
  "usage": "Usage Markdown, see below",
  "licenseName": "Apache 2.0",
  "fineTunable": False,
  "trainingData": [],
  "modelInstanceType": "Unspecified",
  "baseModelInstance": "",
  "externalBaseModelUrl": ""
}

You can also use the API command kaggle models variations init -p /path/to/model-variation to have the API create this file for you for a new model variation.

Contents

We currently support the following metadata fields for model variations.

  • ownerSlug: the slug of the user or organization of the model
  • modelSlug: the existing model's slug
  • instanceSlug: the slug of the variation
  • framework: the variation's framework (possible options: tensorFlow1,tensorFlow2,tfLite,tfJs,pyTorch,jax,coral, ...)
  • overview: a short overview of the variation
  • usage: the variation's usage in markdown syntax (see the template below)
  • fineTunable: whether the variation is fine tunable
  • trainingData: a list of training data in the form of strings, URLs, Kaggle Datasets, etc...
  • modelInstanceType: whether the model variation is a base model, external variant, internal variant, or unspecified
  • baseModelInstance: if this is an internal variant, the {owner-slug}/{model-slug}/{framework}/{variation-slug} of the base model variation
  • externalBaseModelUrl: if this is an external variant, a URL to the base model

Licenses

Here is a list of the available licenses for models:

  • Apache 2.0
  • Attribution 3.0 IGO (CC BY 3.0 IGO)
  • Attribution 3.0 Unported (CC BY 3.0)
  • Attribution 4.0 International (CC BY 4.0)
  • Attribution-NoDerivatives 4.0 International (CC BY-ND 4.0)
  • Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
  • Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
  • Attribution-NonCommercial-ShareAlike 3.0 IGO (CC BY-NC-SA 3.0 IGO)
  • BSD-3-Clause
  • CC BY-NC-SA 4.0
  • CC BY-SA 3.0
  • CC BY-SA 4.0
  • CC0: Public Domain
  • Community Data License Agreement - Permissive - Version 1.0
  • Community Data License Agreement - Sharing - Version 1.0
  • GNU Affero General Public License 3.0
  • GNU Free Documentation License 1.3
  • GNU Lesser General Public License 3.0
  • GPL 2
  • MIT
  • ODC Attribution License (ODC-By)
  • ODC Public Domain Dedication and Licence (PDDL)
  • GPL 3

Usage

The following template variables can be used in this markdown:

  • ${VERSION_NUMBER} is replaced by the version number when rendered
  • ${VARIATION_SLUG} is replaced by the variation slug when rendered
  • ${FRAMEWORK} is replaced by the framework name
  • ${PATH} is replaced by /kaggle/input/<model_slug>/<framework>/<variation_slug>/<version>.
  • ${FILEPATH} is replaced by /kaggle/input/<model_slug>/<framework>/<variation_slug>/<version>/<filename>. This value is only defined if the databundle contain a single file
  • ${URL} is replaced by the absolute URL of the model