I want to use the agent which I trained in from your rl-agents instead of the stablebaseline implementation. How can I use it in a code like this:

import warnings
import gym
import highway_env
from stable_baselines3 import DQN
import json
import os
import cv2
import numpy as np

ACTIONS_ALL = {
0: 'LANE_LEFT',
1: 'IDLE',
2: 'LANE_RIGHT',
3: 'FASTER',
4: 'SLOWER'
}

config = {
"observation": {
"type": "Kinematics",
"features": ["presence", "x", "y", "vx", "vy"],
"normalize": False
}
}

env = gym.make("highway-fast-v0")
env.configure(config)
env.reset()

model = DQN.load(
"C:\Users\davin\Documents\Studium\Bachelorarbeit\davin-holten-bachelor\highway_dqn\highway_dqn\DQNFast2\rl_model_500000_steps.zip")

basic_traces_folder = "basic_traces"
simb_traces_folderRL = "simb_tracesRL"

if not os.path.exists(basic_traces_folder):
os.makedirs(basic_traces_folder)

if not os.path.exists(simb_traces_folderRL):
os.makedirs(simb_traces_folderRL)

fileCounter = 1
Crash = False
critical_distance = False
critical_distanceY = False

for i in range(1,50):
frames = []
steps = 0
done = truncated = False
obs = env.reset()
dest_state = obs.tolist()
Crash = False
critical_distance = False
critical_distanceY = False
videoCounter=i

while not (done or truncated):
    action, _states = model.predict(obs, deterministic=True)
    obs, reward, done, info = env.step(int(action))
    dest_state = obs.tolist()
    check= False
    checkY = False
    steps += 1

   # Trace Creation