update readme

Author: dnth

README.md

@@ -454,31 +454,25 @@ The following is a demo of image inference
 
 
 ## 📝 Pixi Cheat Sheet
-Here are some useful tasks you can run with Pixi.
+Here are some useful tasks you can run with Pixi. You must install pixi on your machine first. See the [installation](#-installation) section for more details.
+For all the commands below, you can add `-e cuda` if you have a CUDA enabled GPU on your machine.
 
-Run a quickstart
+Run a quickstart to check if your environment is setup correctly. By default, this will run in a CPU environment.
 ```bash
 pixi run quickstart
 ```
 
-Smoke test the package
-```bash
-pixi run -e cpu quickstart
-```
+or to run in a CUDA enabled environment
 ```bash
 pixi run -e cuda quickstart
 ```
 
-Train a model
-```bash
-pixi run -e cuda train-model
-```
-
+Live inference with pretrained model on webcam
 ```bash
-pixi run -e cpu train-model
+pixi run -e cuda live-inference-pretrained --webcam
 ```
 
-Run live inference
+Run live inference on a custom onnx model
 ```bash
 pixi run -e cuda live-inference --onnx model.onnx --webcam --provider cuda --class-names classes.txt --inference-size 640
 ```
@@ -495,11 +489,6 @@ pixi run -e cuda live-inference --onnx model.onnx --webcam --provider cuda --cla
 pixi run -e cpu live-inference --onnx model.onnx --input video.mp4 --class-names classes.txt --inference-size 320
 ```
 
-Live inference with pretrained model on webcam
-```bash
-pixi run -e cuda live-inference-pretrained --webcam
-```
-
 Launch Gradio app
 ```bash
 pixi run gradio-demo --model "best_prep.onnx" --classes "classes.txt" --examples "Rock Paper Scissors SXSW.v14i.coco/test"
@@ -509,12 +498,20 @@ pixi run gradio-demo --model "best_prep.onnx" --classes "classes.txt" --examples
 pixi run -e cpu gradio-demo
 ```
 
+Train a model
+```bash
+pixi run -e cuda train-model
+```
+
+```bash
+pixi run -e cpu train-model
+```
+
 Export model to ONNX
 ```bash
 pixi run export --config config.yml --checkpoint model.pth --output model.onnx
 ```
 
 
-
 ## ⚠️ Disclaimer
 I'm not affiliated with the original DEIM authors. I just found the model interesting and wanted to try it out. The changes made here are of my own. Please cite and star the original repo if you find this useful.