diff --git a/src/f5_tts/configs/F5TTS_Base_train.yaml b/src/f5_tts/configs/F5TTS_Base_train.yaml
index d757c5b..fe93332 100644
--- a/src/f5_tts/configs/F5TTS_Base_train.yaml
+++ b/src/f5_tts/configs/F5TTS_Base_train.yaml
@@ -28,6 +28,7 @@ model:
     ff_mult: 2
     text_dim: 512
     conv_layers: 4
+    checkpoint_activations: False # recompute activations and save memory for extra compute
   mel_spec:
     target_sample_rate: 24000
     n_mel_channels: 100
diff --git a/src/f5_tts/configs/F5TTS_Small_train.yaml b/src/f5_tts/configs/F5TTS_Small_train.yaml
index 833c6af..466ee29 100644
--- a/src/f5_tts/configs/F5TTS_Small_train.yaml
+++ b/src/f5_tts/configs/F5TTS_Small_train.yaml
@@ -28,6 +28,7 @@ model:
     ff_mult: 2
     text_dim: 512
     conv_layers: 4
+    checkpoint_activations: False # recompute activations and save memory for extra compute
   mel_spec:
     target_sample_rate: 24000
     n_mel_channels: 100
diff --git a/src/f5_tts/model/backbones/dit.py b/src/f5_tts/model/backbones/dit.py
index 391752a..472af28 100644
--- a/src/f5_tts/model/backbones/dit.py
+++ b/src/f5_tts/model/backbones/dit.py
@@ -105,6 +105,7 @@ class DiT(nn.Module):
         text_dim=None,
         conv_layers=0,
         long_skip_connection=False,
+        checkpoint_activations=False,
     ):
         super().__init__()
 
@@ -127,6 +128,17 @@ class DiT(nn.Module):
         self.norm_out = AdaLayerNormZero_Final(dim)  # final modulation
         self.proj_out = nn.Linear(dim, mel_dim)
 
+        self.checkpoint_activations = checkpoint_activations
+
+    def ckpt_wrapper(self, module):
+        """Code from https://github.com/chuanyangjin/fast-DiT/blob/1a8ecce58f346f877749f2dc67cdb190d295e4dc/models.py#L233-L237"""
+
+        def ckpt_forward(*inputs):
+            outputs = module(*inputs)
+            return outputs
+
+        return ckpt_forward
+
     def forward(
         self,
         x: float["b n d"],  # nosied input audio  # noqa: F722
@@ -152,7 +164,10 @@ class DiT(nn.Module):
             residual = x
 
         for block in self.transformer_blocks:
-            x = block(x, t, mask=mask, rope=rope)
+            if self.checkpoint_activations:
+                x = torch.utils.checkpoint.checkpoint(self.ckpt_wrapper(block), x, t, mask, rope)
+            else:
+                x = block(x, t, mask=mask, rope=rope)
 
         if self.long_skip_connection is not None:
             x = self.long_skip_connection(torch.cat((x, residual), dim=-1))