> This page is for MolMIM, version 1.0.0 (Latest) (default).
> For other versions, use one of these documentation indexes:
> - 1.0.0 (Latest) (default): https://docs.nvidia.com/nim/bionemo/molmim/1.0.0/llms.txt

> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/nim/bionemo/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nim/bionemo/_mcp/server.

# Quickstart Guide

<Note>
This page assumes you have installed and set up [Prerequisite Software](/nim/bionemo/molmim/prerequisites) (Docker, NGC CLI, NGC registry access).
</Note>

1. Pull the NIM container with the following command.

```bash
docker pull nvcr.io/nim/nvidia/molmim:1.0.0
```


2. Run the NIM container with the following command.

```bash
docker run --rm -it --name molmim --runtime=nvidia \
    -e CUDA_VISIBLE_DEVICES=0 \
    -e NGC_CLI_API_KEY \
    -p 8000:8000 \
    nvcr.io/nim/nvidia/molmim:1.0.0
```


This command starts the NIM container and exposes port 8000 for the user to interact with the NIM.

3. Open a new terminal, leaving the current terminal open with the launched service.

4. In the new terminal, wait until the health check end point returns `{"status":"ready"}` before proceeding. This can take a couple of minutes. You can use the following command to query the health check.

```bash
curl -X 'GET' \
    'http://localhost:8000/v1/health/ready' \
    -H 'accept: application/json'
```

5. Run inference to get the embeddings of a molecule from its SMILES string representation and save the output to output.json using the following command.

```bash
curl -X 'POST' \
    'http://localhost:8000/embedding' \
    -H 'accept: application/json' \
    -H 'Content-Type: application/json' \
    -d '{"sequences": ["CC(Cc1ccc(cc1)C(C(=O)O)C)C"]}' > output.json
```

6. View the outputs. You can use the cat tool print the outputs to the command line as with the following command.

```bash
cat output.json
```

However, we recommend installing [`jq`](https://jqlang.github.io/jq/), a command-line tool that can format JSON for improved readability. You can use `jq` to visualize the output from the file:

```bash
jq . output.json
```

or you can pipe the output directly to `jq` as in the following command:

```bash
curl -X 'POST' \
    'http://localhost:8000/embedding' \
    -H 'accept: application/json' \
    -H 'Content-Type: application/json' \
    -d '{"sequences": ["CC(Cc1ccc(cc1)C(C(=O)O)C)C"]}' > output.json
```