From f5c84c52329fd4e09008682ae5cdc2feac570d21 Mon Sep 17 00:00:00 2001
From: Vatsal Birla <vb563488@gmail.com>
Date: Fri, 11 Jul 2025 02:05:13 +0530
Subject: [PATCH] docs: add Quick Start Examples to usage.rst

---
 docs/usage.rst | 27 +++++++++++++++++++++++++++
 1 file changed, 27 insertions(+)

diff --git a/docs/usage.rst b/docs/usage.rst
index f0c718a..e41f1fc 100644
--- a/docs/usage.rst
+++ b/docs/usage.rst
@@ -2,6 +2,33 @@
 Usage
 =====
 
+=======================
+Quick Start Examples 🚀
+=======================
+
+These are the most commonly used `igel` commands for quickly training and using machine learning models from the CLI.
+
+.. code-block:: console
+
+    # 1. Generate a starter config YAML
+    igel init -type "classification" -model "RandomForest" -target "sick"
+
+    # 2. Train the model using your dataset and YAML
+    igel fit -dp path/to/train.csv -yml path/to/igel.yaml
+
+    # 3. Evaluate the trained model
+    igel evaluate -dp path/to/eval.csv
+
+    # 4. Make predictions using the model
+    igel predict -dp path/to/test.csv
+
+    # 5. Run all 3 (fit, evaluate, predict) in one command
+    igel experiment -DP "train.csv eval.csv test.csv" -yml igel.yaml
+
+    # 6. Export model to ONNX
+    igel export -dp model_results/
+
+
 
 you can run this command to get instruction on how to use the model: