Update README.sd-embeddings.md

README.sd-embeddings.md

@@ -12,14 +12,14 @@ Note that SD 1.5 has a different format for embeddings than SDXL. And within SD
 ### SD 1.5 pickletensor embed format
 
 I have observed that .pt embeddings have a dict-of-dicts type format. It looks something like this:
-[
-"string_to_token": {'doesntmatter': 265}, # I dont know why 265, but it usually is
-"string_to_param": {'doesntmatter': tensor([[][768])},
-"name": *string*,
-"step": *string*,
-"sd_checkpoint": *string*,
-"sd_checkpoint_name": *string*
-]
+    [
+    "string_to_token": {'doesntmatter': 265}, # I dont know why 265, but it usually is
+    "string_to_param": {'doesntmatter': tensor([[][768])},
+    "name": *string*,
+    "step": *string*,
+    "sd_checkpoint": *string*,
+    "sd_checkpoint_name": *string*
+    ]
 
 (Note that *string* can be None)
 
@@ -28,16 +28,16 @@ I have observed that .pt embeddings have a dict-of-dicts type format. It looks s
 
 The ones I have seen, have a much simpler format. It is a trivial format compared to SD 1.5:
 
-{ "emb_params": Tensor([][768])}
+    { "emb_params": Tensor([][768])}
 
-### SDXL embed format (safetensor)
+## SDXL embed format (safetensor)
 
 This has an actual spec at: 
 https://huggingface.co/docs/diffusers/using-diffusers/textual_inversion_inference
 But it's pretty simple:
 
 summary:
-{
-"clip_l": Tensor([][768]),
-"clip_g": Tensor([][1280])
-}
+    {
+    "clip_l": Tensor([][768]),
+    "clip_g": Tensor([][1280])
+    }