# Summary of Stable Diffusion embedding format

This file is to be a quick reference for SD embedding file formats.

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])
    }