--- a
+++ b/tests/model_integration_test_manual.py
@@ -0,0 +1,50 @@
+# -*- coding: utf-8 -*-
+# ! /usr/bin/env python
+""" script for quick local testing if a model works inside medigan."""
+# run with python -m tests.model_integration_test_manual
+
+import logging
+
+MODEL_ID = "YOUR_MODEL_ID_HERE"
+MODEL_ID = 23  # "00023_PIX2PIXHD_BREAST_DCEMRI" #"00002_DCGAN_MMG_MASS_ROI"  # "00007_BEZIERCURVE_TUMOUR_MASK"
+NUM_SAMPLES = 2
+OUTPUT_PATH = f"output/{MODEL_ID}/"
+try:
+    from src.medigan.generators import Generators
+
+    generators = Generators()
+except Exception as e:
+    logging.error(f"test_init_generators error: {e}")
+    raise e
+
+generators.generate(
+    model_id=MODEL_ID,
+    num_samples=NUM_SAMPLES,
+    output_path=OUTPUT_PATH,
+    input_path="input/",
+    gpu_id=0,
+    image_size=448,
+    install_dependencies=True,
+)
+
+data_loader = generators.get_as_torch_dataloader(
+    model_id=MODEL_ID,
+    num_samples=NUM_SAMPLES,
+    output_path=OUTPUT_PATH,
+    input_path="input/",
+    gpu_id=0,
+    image_size=448,
+    # prefetch_factor=2, # debugging with torch v2.0.0: This will raise an error for torch DataLoader if num_workers == None at the same time.
+)
+
+print(f"len(data_loader): {len(data_loader)}")
+
+if len(data_loader) != NUM_SAMPLES:
+    logging.warning(
+        f"{MODEL_ID}: The number of samples in the dataloader (={len(data_loader)}) is not equal the number of samples requested (={NUM_SAMPLES})."
+    )
+
+#### Get the object at index 0 from the dataloader
+data_dict = next(iter(data_loader))
+
+print(f"data_dict: {data_dict}")