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CLI Basics

If you want to train, validate or run inference on models and don't need to make any modifications to the code, using YOLO command line interface is the easiest way to get started.

!!! tip "Syntax" bash yolo task=detect mode=train model=s.yaml epochs=1 ... ... ... ... segment infer s-cls.pt classify val s-seg.pt

The experiment arguments can be overridden directly by pass arg=val covered in the next section. You can run any supported task by setting task and mode in cli. === "Training"

task snippet
Detection detect
yolo task=detect mode=train       
Instance Segment segment
yolo task=segment mode=train      
Classification classify
yolo task=classify mode=train    

=== "Inference"

task snippet
Detection detect
yolo task=detect mode=infer       
Instance Segment segment
yolo task=segment mode=infer     
Classification classify
yolo task=classify mode=infer    

=== "Validation"

task snippet
Detection detect
yolo task=detect mode=val        
Instance Segment segment
yolo task=segment mode=val       
Classification classify
yolo task=classify mode=val      

!!! note "" Note: The arguments don't require '--' prefix. These are reserved for special commands covered later

Overriding default config arguments

All global default arguments can be overriden by simply passing them as arguments in the cli. !!! tip "" === "Syntax" yolo task= ... mode= ... {++ arg=val ++}

=== "Example"
    Perform detection training for `10 epochs` with `learning_rate` of `0.01`
    ```
    yolo task=detect mode=train {++ epochs=10 lr0=0.01 ++}

    ```

Overriding default config file

You can override config file entirely by passing a new file. You can create a copy of default config file in your current working dir as follows:

yolo task=init

You can then use special --cfg name.yaml command to pass the new config file

yolo task=detect mode=train {++ --cfg default.yaml ++}

??? example === "Command" yolo task=init yolo task=detect mode=train --cfg default.yaml === "Result" TODO: add terminal output