It is so confused to load textual-inversion sdxl embedding as inference prompt

### Describe the bug

I trained a textual inversion model on SDXL pretrained model ( RealVisXL3.0 ), and then when I want to inference, I use this textual inversion model as a positive prompt to strengthen some aspect of the model.
But when I try to load the RealVisXL3.0 with `from_pretrained()` first and load the textual-inversion model with `load_textual_inversion(),` I get an error. I looked at the relevant information, but there was no good workaround.

### Reproduction

Mycode:
Error:
ValueError: Loaded state dictionary is incorrect: {'text_model.embeddings.position_embedding.weight'
Please verify that the loaded state dictionary of the textual embedding either only has a single key or includes the `string_to_param` input key.

### Logs

```shell
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
Cell In[14], line 3
1 pipe = DiffusionPipeline.from_pretrained("/mnt/asian-t2i/pretrained_models/RealVisXL_V3.0", torch_dtype=torch.float16, use_safetensors=True, variant="fp16")
2 pipe.to("cuda:2")
----> 3 pipe.load_textual_inversion("/mnt/asian-t2i/output/textual-inversion/textual_inversion-sdxl-data1k6-realism/checkpoint-1000/model.safetensors", token="", text_encoder=pipe.text_encoder, tokenizer=pipe.tokenizer)
5 # positive_prompt = '1girl, black hair, solo, sleeveless, denim, plate, ponytail, blurry, cup, indoors, blurry background, table, realistic, turtleneck, belt, pants, long hair, jeans, jewelry, drinking, own hands together, sleeveless shirt, depth of field, mole, shirt, food, holding'
6 positive_prompt = 'a sl_1234# woman with long hair and a white shirt. high quality, Realism, 4K, '

File /opt/conda/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py:118, in validate_hf_hub_args.._inner_fn(*args, **kwargs)
115 if check_use_auth_token:
116 kwargs = smoothly_deprecate_use_auth_token(fn_name=fn.__name__, has_token=has_token, kwargs=kwargs)
--> 118 return fn(*args, **kwargs)

File /mnt/asian-t2i/diffusers/src/diffusers/loaders/textual_inversion.py:402, in TextualInversionLoaderMixin.load_textual_inversion(self, pretrained_model_name_or_path, token, tokenizer, text_encoder, **kwargs)
396 raise ValueError(
397 f"You have passed a state_dict contains {len(state_dicts)} embeddings, and list of tokens of length {len(tokens)} "
398 f"Make sure both have the same length."
399 )
401 # 4. Retrieve tokens and embeddings
--> 402 tokens, embeddings = self._retrieve_tokens_and_embeddings(tokens, state_dicts, tokenizer)
404 # 5. Extend tokens and embeddings for multi vector
405 tokens, embeddings = self._extend_tokens_and_embeddings(tokens, embeddings, tokenizer)

File /mnt/asian-t2i/diffusers/src/diffusers/loaders/textual_inversion.py:217, in TextualInversionLoaderMixin._retrieve_tokens_and_embeddings(tokens, state_dicts, tokenizer)
215 embedding = state_dict["string_to_param"]["*"]
216 else:
--> 217 raise ValueError(
218 f"Loaded state dictionary is incorrect: {state_dict}. \n\n"
219 "Please verify that the loaded state dictionary of the textual embedding either only has a single key or includes the `string_to_param`"
220 " input key."
221 )
223 if token is not None and loaded_token != token:
224 logger.info(f"The loaded token: {loaded_token} is overwritten by the passed token {token}.")

ValueError: Loaded state dictionary is incorrect: {'text_model.embeddings.position_embedding.weight': tensor([[ 0.0016, 0.0020, 0.0002, ..., -0.0013, 0.0007, 0.0015],
[ 0.0042, 0.0029, 0.0002, ..., 0.0010, 0.0015, -0.0012],
[ 0.0018, 0.0007, -0.0012, ..., -0.0029, -0.0009, 0.0026],
...,
[ 0.0216, 0.0055, -0.0101, ..., -0.0065, -0.0029, 0.0037],
[ 0.0188, 0.0073, -0.0077, ..., -0.0025, -0.0009, 0.0057],
[ 0.0330, 0.0281, 0.0288, ..., 0.0160, 0.0102, -0.0310]]), 'text_model.embeddings.token_embedding.weight': tensor([[-0.0012, 0.0369, 0.0221, ..., 0.0159, 0.0046, -0.0220],
[ 0.0152, 0.0261, -0.0132, ..., -0.0037, 0.0002, 0.0121],
[-0.0154, -0.0131, 0.0065, ..., -0.0206, -0.0139, -0.0025],
...,
[ 0.0320, -0.0165, -0.0014, ..., 0.0161, 0.0044, 0.0141],
[ 0.0324, -0.0169, -0.0012, ..., 0.0159, 0.0046, 0.0143],
[ 0.0323, -0.0169, -0.0012, ..., 0.0158, 0.0045, 0.0144]]), 'text_model.encoder.layers.0.layer_norm1.bias': tensor([-6.3965e-02, -1.8945e-01, -6.6406e-02, 1.1578e-01, -1.9409e-02,
-7.6782e-02, -9.2346e-02, 1.5039e-01, -1.5430e-01, 5.3711e-02,
-2.6001e-01, 1.6309e-01, -6.2378e-02, -2.1582e-01, -2.1027e-02,
1.8555e-01, 2.2461e-01, -8.3801e-02, 6.8848e-02, -1.7285e-01,
6.4941e-02, -1.6846e-02, -1.8417e-02, -2.3926e-01, -6.9336e-02,
-4.7913e-02, 2.9907e-01, 1.0107e-01, -7.4268e-01, -5.8624e-02,
-1.4868e-01, 1.6614e-01, 1.8640e-01, 5.3040e-02, 1.5640e-03,
1.1094e+00, 1.6333e-01, 2.9907e-01, 5.7770e-02, 8.7036e-02,
1.0384e-02, 3.3447e-02, -1.1225e-03, -2.0691e-01, 3.9429e-02,
3.0664e-01, -9.5215e-02, -1.0803e-01, 3.2812e-01, 2.4231e-01,
-5.1086e-02, 7.2205e-02, 5.2734e-02, 5.2246e-02, 4.5508e-01,
9.3994e-03, 1.0803e-01, -3.1860e-01, 1.6333e-01, -1.6138e-01,
6.9763e-02, 9.1858e-02, -1.9043e-02, 1.1182e-01, -2.0508e-01,
5.3467e-02, 2.6196e-01, -5.0391e-01, 1.6846e-02, 2.6758e-01,
2.5391e-01, 9.7229e-02, 1.9775e-02, 7.3853e-02, 1.1871e-01,
4.0771e-02, 1.0614e-03, -7.4219e-02, 7.3242e-02, 3.3936e-01,
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-1.8774e-01, 4.0649e-01, -9.6680e-02, 5.7373e-02, -9.1553e-03,
-4.6875e-01, 3.3264e-02, -9.2773e-02, -9.5978e-03, 1.9043e-01,
1.5820e-01, 9.0527e-01, -1.8860e-01, 1.7407e-01, 5.5511e-02,
-1.3574e-01, -4.3701e-02, 7.9163e-02, 1.8774e-01, 6.7322e-02,
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2.8516e-01, 1.9531e-01, -1.3623e-01, 2.4316e-01, -8.0078e-02,
-6.7444e-02, -6.7444e-02, -1.0742e-01, 2.4902e-02, 2.8149e-01,
1.2158e-01, 3.6401e-01, 2.3468e-02, -2.8320e-01, 2.2461e-01,
3.6157e-01, -1.0992e-01, 3.4668e-02, 7.4219e-02, 2.7930e-01,
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1.0791e-01, 5.3467e-02, 2.2583e-03, 2.7359e-02, -1.8872e-01,
8.4534e-02, 5.2002e-02, 2.0605e-01, -1.5234e-01, -8.4534e-02,
8.9905e-02, -8.0688e-02, 1.4734e-01, -1.6129e-02, -4.8584e-02,
2.0142e-01, -1.8347e-01, 2.6538e-01, -3.1250e-01, 9.1309e-02,
2.0325e-01, 1.1096e-01, -1.5625e-02, 3.5962e-01, 2.5757e-02,
-2.1313e-01, -7.0572e-03, -1.2207e-01, 1.9434e-01, 1.4868e-01,
1.2360e-01, 1.8640e-01, 2.5513e-02, 3.4485e-02, 1.1035e-01,
1.4648e-01, 2.2232e-02, -5.9357e-02, -1.3281e-01, 3.4570e-01,
-3.0664e-01, 7.9346e-01, 3.9551e-02, -1.4648e-01, 6.5491e-02,
1.7090e-02, -2.0203e-01, 2.3956e-02, -4.0527e-02, -4.6631e-02,
2.1204e-01, -8.7891e-02, -1.6138e-01, 6.9336e-02, -2.5024e-01,
5.2460e-02, -2.3743e-01, 1.8555e-01, 7.2754e-02, 4.7363e-02,
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1.2164e-01, -2.1094e-01, 4.1968e-01, 1.4062e-01, 1.7493e-01,
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3.4424e-02, -1.1572e-01, -2.2278e-01, -1.0693e-01, 9.7656e-02,
3.4668e-02, -1.4307e+00, -1.1063e-02, 1.9434e-01, 1.0938e-01,
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3.8330e-01, 6.4087e-02, 1.5820e-01, 1.8326e-02, -2.0599e-03,
1.6022e-02, -4.8584e-02, -1.0345e-01, 1.5747e-01, -1.9684e-02,
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7.2205e-02, 7.6172e-02, -1.3074e-01, -1.9714e-01, -1.7407e-01,
1.3867e-01, 1.5625e-01, 3.2043e-03, -3.8574e-02, -1.8347e-01,
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3.3203e-01, -8.5510e-02, -1.2109e-01, -4.5264e-01, -2.6978e-01,
2.8882e-01, 2.4646e-01, -1.1719e-01, 3.4570e-01, 1.4746e-01,
4.0527e-02, -4.2969e-02, -7.8174e-01, 3.0289e-02, -1.6760e-01,
1.4465e-02, 3.2422e-01, 2.3828e-01, -1.0443e-01, 6.3477e-02,
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1.0010, 1.0156, 0.9727, 0.9336, 0.9375, 0.9888, 0.9570, 1.0400, 0.9951,
0.9531, 1.1328, 1.0078, 0.9658, 0.9692, 0.9531, 0.9736, 1.0391, 0.9995,
0.9771, 0.9834, 0.9771])}.

Please verify that the loaded state dictionary of the textual embedding either only has a single key or includes the `string_to_param` input key.
```

### System Info

diffusers version:
Name: diffusers
Version: 0.27.0.dev0

### Who can help?

@sayakpaul @yiyixuxu @DN6

Start in src/diffusers/loaders/textual_inversion.py, especially load_textual_inversion() and _retrieve_tokens_and_embeddings(), using the reported SDXL checkpoint format and ValueError as the reproduction. Determine the expected handling for this state dictionary and verify that loading it through the reported pipeline succeeds without the error.

Vom Indexierungsmodell aus dem Issue-Text verfasst.