Add docs for Carton export (#336)

docs/user_guide/command_line_interface.md

@@ -17,6 +17,7 @@ Ludwig provides several functions through its command line interface.
 | [`collect_weights`](#collect_weights)         | Collects tensors containing a pretrained model weights                            |
 | [`collect_activations`](#collect_activations) | Collects tensors for each datapoint using a pretrained model                      |
 | [`export_torchscript`](#export_torchscript)   | Exports Ludwig models to Torchscript                                              |
+| [`export_carton`](#export_carton)             | Exports Ludwig models to Carton                                                   |
 | [`export_neuropod`](#export_neuropod)         | Exports Ludwig models to Neuropod                                                 |
 | [`export_mlflow`](#export_mlflow)             | Exports Ludwig models to MLflow                                                   |
 | [`preprocess`](#preprocess)                   | Preprocess data and saves it into HDF5 and JSON format                            |
@@ -973,6 +974,43 @@ optional arguments:
 
 For more information, see [TorchScript Export](/user_guide/model_export/#torchscript-export)
 
+# export_carton
+
+A Ludwig model can be exported as a [Carton](https://carton.run/), which allows it to be run from several programming languages (including C, C++, Rust, and more).
+
+In order to export a Ludwig model to Carton, first make sure the `cartonml` package is installed in your environment (`pip install cartonml-nightly`), then run the following command:
+
+```bash
+ludwig export_carton [options]
+```
+
+or with:
+
+```bash
+python -m ludwig.export carton [options]
+```
+
+These are the available arguments:
+
+```
+usage: ludwig export_carton [options]
+
+This script loads a pretrained model and saves it as a Carton.
+
+options:
+  -h, --help            show this help message and exit
+  -m MODEL_PATH, --model_path MODEL_PATH
+                        model to load
+  -mn MODEL_NAME, --model_name MODEL_NAME
+                        model name
+  -od OUTPUT_PATH, --output_path OUTPUT_PATH
+                        path where to save the export model
+  -l {critical,error,warning,info,debug,notset}, --logging_level {critical,error,warning,info,debug,notset}
+                        the level of logging to use
+```
+
+For more information, see [Carton Export](/user_guide/model_export/#carton-export)
+
 # export_neuropod
 
 A Ludwig model can be exported as a [Neuropod](https://github.com/uber/neuropod), a mechanism that allows it to be executed in a framework agnostic way.

docs/user_guide/model_export.md

@@ -170,6 +170,33 @@ For the majority of features, NaNs are handled by the preprocessor in the same w
 
 HuggingFace models are not yet supported for TorchScript export, though we are working on it!
 
+## Carton Export
+
+[Carton](https://carton.run/) is a library that allows users to efficiently run ML models from several programming languages (including C, C++, Rust, and more).
+
+A subset of Ludwig Models can be exported to Carton. In addition to the model itself, the preprocessing and postprocessing steps are included in the exported model as well, ensuring that the model can be used for inference in a production environment out-of-the-box.
+
+To get started, simply run the [`export_carton`](/latest/user_guide/command_line_interface/#export_carton) command:
+
+```
+ludwig export_carton -m=results/experiment_run/model
+```
+This will produce a file that can be loaded by Carton from any supported programming language.
+
+For example, from Python, you can load and run the model as follows:
+
+```py
+import cartonml as carton
+
+async def main():
+    model = await carton.load("/path/to/model.carton")
+    output = await model.infer({
+        "x": np.zeros(5)
+    })
+```
+
+See the [Carton quickstart guide](https://carton.run/quickstart) for usage from other programming languages.
+
 ## Triton Export
 
 Coming soon...