Create README.sd-embeddings.md

README.sd-embeddings.md

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+# Summary of Stable Diffusion embedding format
+
+Note: there are a bunch of files here that have "embedding" in their names. However, they cannot be used as Stable Diffusion Embeddings.
+
+I do include some tools, such as *generate-embedding.py* and *generate-embeddingXL.py*, that are intended
+to explore the actual inference tool formatted embedding file types. Therefore, I'm taking some time to document
+the little I know about the format of those files
+
+## Stable Diffusion v1.5
+Note that SD 1.5 has a different format for embeddings than SDXL. And within SD 1.5, there are two different formats
+
+### 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*
+]
+
+(Note that *string* can be None)
+
+
+### SD 1.5 safetensor embed format
+
+The ones I have seen, have a much simpler format. It is a trivial format compared to SD 1.5:
+
+{ "emb_params": Tensor([][768])}
+
+### 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])
+}