diff --git a/src/cdtools/datasets/ptycho_2d_dataset.py b/src/cdtools/datasets/ptycho_2d_dataset.py
index 6631cd6..3825d6d 100644
--- a/src/cdtools/datasets/ptycho_2d_dataset.py
+++ b/src/cdtools/datasets/ptycho_2d_dataset.py
@@ -1,15 +1,16 @@
+import warnings
+from copy import copy, deepcopy
+import pathlib
+
+import h5py
 import numpy as np
 import torch as t
-from copy import copy
-import h5py
-import pathlib
+
 from cdtools.datasets import CDataset
 from cdtools.datasets.random_selection import random_selection
 from cdtools.tools import data as cdtdata
 from cdtools.tools import plotting
-from matplotlib import pyplot as plt
 from cdtools.tools import analysis
-from copy import deepcopy
 
 __all__ = ['Ptycho2DDataset']
 
@@ -124,9 +125,9 @@ class Ptycho2DDataset(CDataset):
         self.translations = self.translations.to(*args, **kwargs)
         self.patterns = self.patterns.to(*args, **kwargs)
 
-
     # It sucks that I can't reuse the base factory method here,
     # perhaps there is a way but I couldn't figure it out.
+
     @classmethod
     def from_cxi(cls, cxi_file, cut_zeros=True, load_patterns=True):
         """Generates a new Ptycho2DDataset from a .cxi file directly
@@ -148,7 +149,7 @@ class Ptycho2DDataset(CDataset):
         """
         # If a bare string is passed
         if isinstance(cxi_file, str) or isinstance(cxi_file, pathlib.Path):
-            with h5py.File(cxi_file,'r') as f:
+            with h5py.File(cxi_file, 'r') as f:
                 return cls.from_cxi(f, cut_zeros=cut_zeros, load_patterns=load_patterns)
 
         # Generate a base dataset
@@ -164,10 +165,15 @@ class Ptycho2DDataset(CDataset):
             patterns, axes = cdtdata.get_data(cxi_file, cut_zeros=cut_zeros)
             dataset.patterns = t.as_tensor(patterns)
             if dataset.patterns.dtype == t.float64:
-                raise NotImplementedError('64-bit floats are not supported and precision will not be retained in reconstructions! Please explicitly convert your data to 32-bit or submit a pull request')
-            
+                # If the data is 64-bit, we need to convert it to 32-bit
+                # because 64-bit floats are not supported in reconstructions
+                dataset.patterns = dataset.patterns.to(dtype=t.float32)
+                warnings.warn(
+                    "64-bit floats are not supported and precision will not be retained in reconstructions and were converted to t.float32! "
+                    "If you would like to have 64-bit support, please open an issue or submit a pull request."
+                )
             dataset.axes = axes
-            
+
             if dataset.mask is None:
                 dataset.mask = t.ones(dataset.patterns.shape[-2:]).to(dtype=t.bool)
 
@@ -176,9 +182,8 @@ class Ptycho2DDataset(CDataset):
             dataset.intensities = t.as_tensor(intensities, dtype=t.float32)
         except KeyError:
             dataset.intensities = None
-            
-        return dataset
 
+        return dataset
 
     def to_cxi(self, cxi_file):
         """Saves out a Ptycho2DDataset as a .cxi file
diff --git a/tests/test_datasets.py b/tests/test_datasets.py
index 3bb91be..8999117 100644
--- a/tests/test_datasets.py
+++ b/tests/test_datasets.py
@@ -1,12 +1,16 @@
+import datetime
+import itertools
+import os
+from copy import deepcopy
+
+import h5py
+import numpy as np
+import pytest
+import torch as t
+
 from cdtools.datasets import CDataset, Ptycho2DDataset
 from cdtools.tools import data as cdtdata
-import numpy as np
-import torch as t
-import h5py
-import datetime
-from copy import deepcopy
-import pytest
-import itertools
+
 
 #
 # We start by testing the CDataset base class
@@ -220,6 +224,40 @@ def test_Ptycho2DDataset_from_cxi(test_ptycho_cxis):
         assert t.allclose(t.tensor(expected['translations']),dataset.translations)
 
 
+def test_Ptycho2DDataset_from_cxi_64bit(test_ptycho_cxis):
+    """Test that we can load a 64-bit cxi file. Should issue
+    a warning, but still load the data."""
+
+    # create test patterns and translations
+    np.random.seed(42)
+    patterns = np.random.rand(20, 256, 256).astype(np.float64)
+    translations = np.random.rand(20, 3).astype(np.float64)
+
+    dataset = Ptycho2DDataset(translations, patterns)
+    dataset.detector_geometry = {
+        'distance': 0.1,  # in meters
+        'basis': t.tensor([
+            [-0e-06, -13.5e-06 * 4],
+            [-13.5e-06 * 4, 0e-06],
+            [0e-06, 0e-06]
+        ]),
+        'corner': None
+    }
+    dataset.wavelength = 1.6891579427792915e-09  # in meters
+    # and save to a temp file
+    dataset.to_cxi('test_Ptycho2DDataset_from_cxi_64bit.cxi')
+
+    with pytest.warns(UserWarning, match='64-bit floats'):
+        dataset_64bit = Ptycho2DDataset.from_cxi('test_Ptycho2DDataset_from_cxi_64bit.cxi')
+
+    # Check that the data is loaded correctly
+    assert dataset_64bit.patterns.dtype == t.float32
+    assert dataset_64bit.translations.dtype == t.float32
+
+    # delete the created test file
+    os.remove('test_Ptycho2DDataset_from_cxi_64bit.cxi')
+
+
 def test_Ptycho2DDataset_to_cxi(test_ptycho_cxis, tmp_path):
     for cxi, expected in test_ptycho_cxis:
         print('loading dataset')