support for ckpt inversions

[ssube]

Add support for ckpt textual inversions with multiple vectors.

The https://huggingface.co/sd-concepts-library inversions have a single layer:

>>> t2["<jungle-punk>"].shape
torch.Size([768])

While most of the inversions/embeddings on Civitai have more than one:

>>> t = torch.load("autumn.ckpt")
>>> t["string_to_param"]["*"].shape
torch.Size([5, 768])
>>> t = torch.load("ghostly.ckpt")
>>> t["string_to_param"]["*"].shape
torch.Size([10, 768])

By generating a token for each [768] vector in the ckpt, it's possible to embed them in an ONNX model and control each layer's strength separately (using LPW or by giving the token more than once).

ghostly-0, ghostly-1, ghostly-2, ghostly-3, ghostly-4, ghostly-5, ghostly-6, ghostly-7, ghostly-8, ghostly-9, ghostly-0, ghostly-1, ghostly-2, ghostly-3, ghostly-4, ghostly-5, ghostly-6, ghostly-7, ghostly-8, ghostly-9, ...
autumn-0, autumn-1, autumn-2, autumn-3, autumn-4, autumn-0, autumn-1, autumn-2, autumn-3, autumn-4,

The only real disadvantage is needing to use more than one token, as far as I can tell.

[sonarcloud]

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