> ## Documentation Index
> Fetch the complete documentation index at: https://docs.unstructured.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Models

> Depending on your need, `Unstructured` provides OCR-based and Transformer-based models to detect elements in the documents. The models are useful to detect the complex layout in the documents and predict the element types.

**Basic usage:**

```python theme={null}
elements = partition(filename=filename,
                     strategy="hi_res",
                     hi_res_model_name="yolox")
```

<Note>
  * To use any model with the partition, set the `strategy` to `hi_res` as shown above.

  * To maintain the consistency between the `unstructured` and `unstructured-api` libraries, we are deprecating the `model_name` parameter. Please use `hi_res_model_name` parameter when specifying a model.
</Note>

The `hi_res_model_name` parameter supports the `yolox` and `detectron2_onnx` arguments.

## Using a Non-Default Model

`Unstructured` will download the model specified in `UNSTRUCTURED_HI_RES_MODEL_NAME` environment variable. If not defined, it will download the default model.

There are three ways you can use the non-default model as follows:

1. Store the model name in the environment variable

```python theme={null}
import os
from unstructured.partition.pdf import partition_pdf

os.environ["UNSTRUCTURED_HI_RES_MODEL_NAME"] = "yolox"

out_yolox = partition_pdf("example-docs/pdf/layout-parser-paper-fast.pdf", strategy="hi_res")

```

2. Pass the model name in the `partition` function.

```python theme={null}
filename = "example-docs/pdf/layout-parser-paper-fast.pdf"

elements = partition(filename=filename,
                     strategy="hi_res",
                     hi_res_model_name="yolox")

```

3. Use [unstructured-inference](https://github.com/Unstructured-IO/unstructured-inference) library.

```python theme={null}
from unstructured_inference.models.base import get_model
from unstructured_inference.inference.layout import DocumentLayout

model = get_model("yolox")
layout = DocumentLayout.from_file("sample-docs/layout-parser-paper.pdf", detection_model=model)

```