> For the complete documentation index, see [llms.txt](https://vaya97chandni.gitbook.io/pesidious/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://vaya97chandni.gitbook.io/pesidious/howto/train-models-against-my-classifier.md).

# Train models against your custom classifier

Currently, Pesidious uses a sample classifier to train the models that can generate evasive malware and evade this classifier. 

You can add your own classifier to the tool in order to train the models against it. Following are the steps to add your own classifier

### Step 1: Create a config file 

Create a config file called `pesidious.congif` in the home of your machine. 

### Step 2: Populate the config file

Add the path to your local saved model (pickle file) or configuration for your remote model

```
[Local-AI-model]
saved_model = /path/to/your/saved/model
Threshold = <threshold for classification>

[Remote-AI-model]
URL = 
Username = 
Password = 
Version = 
Threshold = 
```

### Step 3: Modify the tool to query your model

Modify the function `get_score_load(bytez)` in `gym_malware/envs/utils/interface.py` to get the score from your classifier

```python
def get_score_local(bytez):
    # local_model = model saved from pesidious.config
    score = local_model.predict(  ) #modify this line to get score from your model
    return score
```