---
title: "Model Repository"
description: "Model Repository is central storage for a model's weights and configuration files, backed by an E2E Object Storage bucket that a Model Endpoint downloads from."
content_type: "overview"
product: "model-repository"
platform: "TIR"
url: "/tir/model-repository/"
---

# Model Repository

Use a Model Repository to keep the weight and configuration files of a custom or fine-tuned model in one place. You can store, version, and share the model there. You can also create a [Model Endpoint](/tir/model-endpoints/) that serves it through a REST API or gRPC. A repository stores model files, and a Model Endpoint is the running service that answers requests using files from a repository. A repository is useful on its own as well.

Each repository is backed by a bucket in E2E Object Storage (EOS). You can work with it as you would with a cloud file system. A model in TIR is a directory in the bucket. A repository takes any file, in any structure, file format, or framework.

You move files in and out through the portal, the MinIO CLI (`mc`), `s3cmd`, or the Python SDK, rather than mounting the repository like a disk. A Model Endpoint downloads from the repository when it starts. A repository grows with its files, so its size always matches what you store.

When you create a repository, you choose where its bucket comes from. It can be a new bucket that TIR creates, one of your own EOS buckets, or an EOS bucket that another account owns.

## Where to find it

In TIR, open your project. In the side menu, under **Inference**, select **Model Repository**. You see the repositories of the current project and region. The dashboard also has a **Create Model Repo** shortcut.

## What you can do

### Create and connect

- [Create a repository](/tir/model-repository/how-to/create-a-repository/) with a name, a model type, and a bucket.
- [Use an existing or external bucket](/tir/model-repository/how-to/use-an-existing-or-external-bucket/) for a repository.
- [Find a repository's access keys and endpoint](/tir/model-repository/how-to/find-the-keys-and-endpoint-of-a-repository/) to connect an S3 tool or the SDK.
- [Connect to a repository with the MinIO CLI or s3cmd](/tir/model-repository/how-to/connect-to-a-repository-with-an-s3-tool/) using the ready-made commands on the **Using CLI** tab.

### Work with model files

- [Upload model files](/tir/model-repository/how-to/upload-model-files/) with the portal, the MinIO CLI, s3cmd, or the Python SDK.
- [Browse, download, and delete files](/tir/model-repository/how-to/browse-download-and-delete-files/) on the **Model Files** tab.
- [Use a repository from an instance or notebook](/tir/model-repository/how-to/use-a-repository-from-an-instance-or-notebook/) to download a model or save a trained one.

### Serve and train

- [Use a repository from a Model Endpoint](/tir/model-repository/how-to/use-a-repository-from-a-model-endpoint/) so the endpoint downloads the model when it starts.
- [Store fine-tuned model output](/tir/model-repository/how-to/store-fine-tuned-model-output/) and continue training from a checkpoint.

### Delete

- [Delete a repository](/tir/model-repository/how-to/delete-a-repository/) when you are finished with it.

## Use the API

The TIR API reference lists the repository operations in [Model Repository](/api/tir/models/model-repository/).

## Where to start

Start with [Get started with Model Repository](/tir/model-repository/get-started/). It creates a repository and uploads a first model. For help with a message, see [Troubleshooting Model Repository](/tir/model-repository/troubleshooting/model-repository/). The [Model Repository FAQ](/tir/model-repository/faq/) has short answers about file formats, versions, access, and billing.