diff --git a/comfy/utils.py b/comfy/utils.py
index b35062824..c901347c4 100644
--- a/comfy/utils.py
+++ b/comfy/utils.py
@@ -50,7 +50,16 @@ def load_torch_file(ckpt, safe_load=False, device=None):
     if device is None:
         device = torch.device("cpu")
     if ckpt.lower().endswith(".safetensors") or ckpt.lower().endswith(".sft"):
-        sd = safetensors.torch.load_file(ckpt, device=device.type)
+        try:
+            sd = safetensors.torch.load_file(ckpt, device=device.type)
+        except Exception as e:
+            if len(e.args) > 0:
+                message = e.args[0]
+                if "HeaderTooLarge" in message:
+                    raise ValueError("{}\n\nFile path: {}\n\nThe safetensors file is corrupt or invalid. Make sure this is actually a safetensors file and not a ckpt or pt or other filetype.".format(message, ckpt))
+                if "MetadataIncompleteBuffer" in message:
+                    raise ValueError("{}\n\nFile path: {}\n\nThe safetensors file is incomplete. Check the file size and make sure you have copied/downloaded it correctly.".format(message, ckpt))
+            raise e
     else:
         if safe_load or ALWAYS_SAFE_LOAD:
             pl_sd = torch.load(ckpt, map_location=device, weights_only=True)
diff --git a/latent_preview.py b/latent_preview.py
index 07f9cc68e..95d3cb733 100644
--- a/latent_preview.py
+++ b/latent_preview.py
@@ -12,7 +12,10 @@ MAX_PREVIEW_RESOLUTION = args.preview_size
 def preview_to_image(latent_image):
         latents_ubyte = (((latent_image + 1.0) / 2.0).clamp(0, 1)  # change scale from -1..1 to 0..1
                             .mul(0xFF)  # to 0..255
-                            ).to(device="cpu", dtype=torch.uint8, non_blocking=comfy.model_management.device_supports_non_blocking(latent_image.device))
+                            )
+        if comfy.model_management.directml_enabled:
+                latents_ubyte = latents_ubyte.to(dtype=torch.uint8)
+        latents_ubyte = latents_ubyte.to(device="cpu", dtype=torch.uint8, non_blocking=comfy.model_management.device_supports_non_blocking(latent_image.device))
 
         return Image.fromarray(latents_ubyte.numpy())