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+## Configuring UDF on ONNX placeholder
+Open Neural Network Exchange [(ONNX)](https://onnx.ai/) is an open format built to represent machine learning models. . Using ONNX, you can make transformations, and write User Defined Functions (UDFs) in the Dozer configuration file to perform SQL transformation. Let's set these configurations step by step.
+
+#### Write the ONNX model
+You can write the ONNX models, by using pre-trained models, and services, or by converting models from various frameworks. For more details about the ONNX models follow this [ONNX tutorial](https://github.com/onnx/models).
+
+To convert the model in ONNX format you can use the Pytorch library. 
+Install Pytorch in your system, in order to use its functionalities.
+You can organize the models in a separate folder, named model. In this folder, put the Python file. 
+
+The first step, is to run the Python file, with this command:
+```bash
+python3 onnx_modeling.py
+```
+where onnx_modeling.py is the model in Python. As a result, it generates the .onnx file that contains data in ONNX format.
+
+#### Configure the UDFs in Dozer
+In the ```dozer_config.yaml``` file, you can configure the udfs, similar to this structure:
+
+``` bash
+udfs:
+  - name: torch_jit
+    config: !Onnx
+      path: ./model/sum.onnx
+```
+The ```config: !Onnx``` supports the transformation from an ONNX model to a UDFs schema. 
+The ```path``` refers to the ```.onnx``` file, and the ```torch_jit``` corresponds to the name of the transformation performed.
+
+#### Perform the SQL transformation
+In the ```dozer_config.yaml``` file, you can perform the SQL transformation, similar to this structure:
+
+```SQL
+sql: |
+  SELECT torch_jit(col1, col2, col3, col4) INTO res
+  FROM onnx_test;
+
+```
+This transformation is based on the UDFs structure. The result will be put in the endpoint named ```res```.
+
+Check the [use case](https://github.com/getdozer/dozer-samples/tree/main/usecases/onnx) in Dozer for more implementation details of this UDFs transformation.