diff --git a/hls4ml/utils/example_models.py b/hls4ml/utils/example_models.py
index 5fefbd662b..657f14325b 100644
--- a/hls4ml/utils/example_models.py
+++ b/hls4ml/utils/example_models.py
@@ -6,17 +6,18 @@
 
 from .config import create_config
 
+ORGANIZATION = 'fastmachinelearning'
+BRANCH = 'master'
+
 
 def _load_data_config_avai(model_name):
     """
     Check data and configuration availability for each model from this file:
 
-    https://github.com/hls-fpga-machine-learning/example-models/blob/master/available_data_config.json
+    https://github.com/fastmachinelearning/example-models/blob/master/available_data_config.json
     """
 
-    link_to_list = (
-        'https://raw.githubusercontent.com/hls-fpga-machine-learning/example-models/master/available_data_config.json'
-    )
+    link_to_list = f'https://raw.githubusercontent.com/{ORGANIZATION}/example-models/{BRANCH}/available_data_config.json'
 
     temp_file, _ = urlretrieve(link_to_list)
 
@@ -73,12 +74,8 @@ def _load_example_data(model_name):
     input_file_name = filtered_name + "_input.dat"
     output_file_name = filtered_name + "_output.dat"
 
-    link_to_input = (
-        'https://raw.githubusercontent.com/hls-fpga-machine-learning/example-models/master/data/' + input_file_name
-    )
-    link_to_output = (
-        'https://raw.githubusercontent.com/hls-fpga-machine-learning/example-models/master/data/' + output_file_name
-    )
+    link_to_input = f'https://raw.githubusercontent.com/{ORGANIZATION}/example-models/{BRANCH}/data/' + input_file_name
+    link_to_output = f'https://raw.githubusercontent.com/{ORGANIZATION}/example-models/{BRANCH}/data/' + output_file_name
 
     urlretrieve(link_to_input, input_file_name)
     urlretrieve(link_to_output, output_file_name)
@@ -91,9 +88,7 @@ def _load_example_config(model_name):
 
     config_name = filtered_name + "_config.yml"
 
-    link_to_config = (
-        'https://raw.githubusercontent.com/hls-fpga-machine-learning/example-models/master/config-files/' + config_name
-    )
+    link_to_config = f'https://raw.githubusercontent.com/{ORGANIZATION}/example-models/{BRANCH}/config-files/' + config_name
 
     # Load the configuration as dictionary from file
     urlretrieve(link_to_config, config_name)
@@ -110,7 +105,7 @@ def fetch_example_model(model_name, backend='Vivado'):
     Download an example model (and example data & configuration if available) from github repo to working directory,
     and return the corresponding configuration:
 
-    https://github.com/hls-fpga-machine-learning/example-models
+    https://github.com/fastmachinelearning/example-models
 
     Use fetch_example_list() to see all the available models.
 
@@ -122,8 +117,8 @@ def fetch_example_model(model_name, backend='Vivado'):
         dict: Dictionary that stores the configuration to the model
     """
 
-    # Initilize the download link and model type
-    download_link = 'https://raw.githubusercontent.com/hls-fpga-machine-learning/example-models/master/'
+    # Initialize the download link and model type
+    download_link = f'https://raw.githubusercontent.com/{ORGANIZATION}/example-models/{BRANCH}/'
     model_type = None
     model_config = None
 
@@ -131,6 +126,9 @@ def fetch_example_model(model_name, backend='Vivado'):
     if '.json' in model_name:
         model_type = 'keras'
         model_config = 'KerasJson'
+    elif '.h5' in model_name:
+        model_type = 'keras'
+        model_config = 'KerasH5'
     elif '.pt' in model_name:
         model_type = 'pytorch'
         model_config = 'PytorchModel'
@@ -158,11 +156,12 @@ def fetch_example_model(model_name, backend='Vivado'):
 
     if _config_is_available(model_name):
         config = _load_example_config(model_name)
+        config[model_config] = model_name  # Ensure that paths are correct
     else:
         config = _create_default_config(model_name, model_config, backend)
 
     # If the model is a keras model then have to download its weight file as well
-    if model_type == 'keras':
+    if model_type == 'keras' and '.json' in model_name:
         model_weight_name = model_name[:-5] + "_weights.h5"
 
         download_link_weight = download_link + model_type + '/' + model_weight_name
@@ -174,7 +173,7 @@ def fetch_example_model(model_name, backend='Vivado'):
 
 
 def fetch_example_list():
-    link_to_list = 'https://raw.githubusercontent.com/hls-fpga-machine-learning/example-models/master/available_models.json'
+    link_to_list = f'https://raw.githubusercontent.com/{ORGANIZATION}/example-models/{BRANCH}/available_models.json'
 
     temp_file, _ = urlretrieve(link_to_list)
 
diff --git a/test/pytest/test_fetch_example.py b/test/pytest/test_fetch_example.py
new file mode 100644
index 0000000000..6e640a94a0
--- /dev/null
+++ b/test/pytest/test_fetch_example.py
@@ -0,0 +1,32 @@
+import ast
+import io
+from contextlib import redirect_stdout
+from pathlib import Path
+
+import pytest
+
+import hls4ml
+
+test_root_path = Path(__file__).parent
+
+
+@pytest.mark.parametrize('backend', ['Vivado', 'Vitis', 'Quartus'])
+def test_fetch_example_utils(backend):
+    f = io.StringIO()
+    with redirect_stdout(f):
+        hls4ml.utils.fetch_example_list()
+    out = f.getvalue()
+
+    model_list = ast.literal_eval(out)  # Check if we indeed got a dictionary back
+
+    assert 'qkeras_mnist_cnn.json' in model_list['keras']
+
+    # This model has an example config that is also downloaded. Stored configurations don't set "Backend" value.
+    config = hls4ml.utils.fetch_example_model('qkeras_mnist_cnn.json', backend=backend)
+    config['KerasJson'] = 'qkeras_mnist_cnn.json'
+    config['KerasH5']
+    config['Backend'] = backend
+    config['OutputDir'] = str(test_root_path / f'hls4mlprj_fetch_example_{backend}')
+
+    hls_model = hls4ml.converters.keras_to_hls(config)
+    hls_model.compile()  # For now, it is enough if it compiles, we're only testing downloading works as expected