Quickstart

First we will create a virtual environment with anaconda.
If you do not have anaconda installed, please check the installation instructions here.
```
   $ conda create --name probe_env python=3.8
```
Next we will activate the virtual environment.
```
   $ conda activate probe_env
```
Once we are done with that, we will clone this github repository and cd into it.
```
   $ git clone https://github.com/giganticode/inspect.git && cd inspect/
```
Next we will install all the necessary packages in the requirements.txt file
```
   $ pip3 install -r requirements.txt
```
We will then begin generating input feature vectors from the pre-trained model weights.
```
   $ CUDA_VISIBLE_DEVICES=0 python3 probe_extractor.py
```

Finally, we will use the pre-trained vectors to make some predictions.

   $ CUDA_VISIBLE_DEVICES=0 python3 probe_classifier.py > results.txt

Hurray! You're done! 🎉
The final task accuracies of each model (layer by layer) will be saved in results.txt file.

NOTE: In steps 5 & 6, we assume that you have access to a gpu with the cuda toolkit installed. If you are using a cpu instead, you can simply run the python scripts without the CUDA_VISIBLE_DEVICES=0 part.