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+# Examples
+
+We provide minimal working examples on how to perform various common tasks with normalizing flows.
+We use Real NVP as an example, but you can replace it with any other bijections from `normalizing_flows.bijections`.
+
+## Training a normalizing flow on a fixed dataset
+```python
+import torch
+from normalizing_flows import Flow
+from normalizing_flows.bijections import RealNVP
+
+torch.manual_seed(0)
+
+# We support arbitrary event and batch shapes
+event_shape = (2, 3)
+batch_shape = (5, 7)
+x_train = torch.randn(size=(*batch_shape, *event_shape))
+
+bijection = RealNVP(event_shape=event_shape)
+flow = Flow(bijection)
+
+flow.fit(x_train, show_progress=True)
+```
+
+## Computing the log determinant of the Jacobian transformation given a Flow
+```python
+import torch
+from normalizing_flows import Flow
+from normalizing_flows.bijections import RealNVP
+
+torch.manual_seed(0)
+
+batch_shape = (5, 7)
+event_shape = (2, 3)
+x = torch.randn(size=(*batch_shape, *event_shape))
+z = torch.randn(size=(*batch_shape, *event_shape))
+
+bijection = RealNVP(event_shape=event_shape)
+flow = Flow(bijection)
+
+_, log_det_forward = flow.bijection.forward(x)
+# log_det_forward.shape == batch_shape
+
+_, log_det_inverse = flow.bijection.inverse(z)
+# log_det_inverse.shape == batch_shape
+```
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