Informer not working on basic example
Author: SlimakSlimak
Pull request: no

### System Info

I am trying minimal example code of Informer specified on HuggingFace website: https://huggingface.co/docs/transformers/model_doc/informer 
however I am getting this error while running that:
```
  File "C:\Users\User\anaconda3\lib\site-packages\torch\nn\modules\linear.py", line 114, in forward
    return F.linear(input, self.weight, self.bias)

RuntimeError: mat1 and mat2 shapes cannot be multiplied (1536x23 and 22x32)
```
I am using 4.27.4 version of transformers library.

The code from website used: 
```
from huggingface_hub import hf_hub_download
import torch
from transformers import InformerModel

file = hf_hub_download(
    repo_id="kashif/tourism-monthly-batch", filename="train-batch.pt", repo_type="dataset"
)
batch = torch.load(file)

model = InformerModel.from_pretrained("huggingface/informer-tourism-monthly")

# during training, one provides both past and future values
# as well as possible additional features
outputs = model(
    past_values=batch["past_values"],
    past_time_features=batch["past_time_features"],
    past_observed_mask=batch["past_observed_mask"],
    static_categorical_features=batch["static_categorical_features"],
    static_real_features=batch["static_real_features"],
    future_values=batch["future_values"],
    future_time_features=batch["future_time_features"],
)

last_hidden_state = outputs.last_hidden_state
```

The full traceback: 
```
outputs = model(

  File "C:\Users\User\anaconda3\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)

  File "C:\Users\User\anaconda3\lib\site-packages\transformers\models\informer\modeling_informer.py", line 1870, in forward
    outputs = self.model(

  File "C:\Users\User\anaconda3\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)

  File "C:\Users\User\anaconda3\lib\site-packages\transformers\models\informer\modeling_informer.py", line 1704, in forward
    encoder_outputs = self.encoder(

  File "C:\Users\User\anaconda3\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)

  File "C:\Users\User\anaconda3\lib\site-packages\transformers\models\informer\modeling_informer.py", line 1178, in forward
    hidden_states = self.value_embedding(inputs_embeds)

  File "C:\Users\User\anaconda3\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)

  File "C:\Users\User\anaconda3\lib\site-packages\transformers\models\informer\modeling_informer.py", line 305, in forward
    return self.value_projection(x)

  File "C:\Users\User\anaconda3\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)

  File "C:\Users\User\anaconda3\lib\site-packages\torch\nn\modules\linear.py", line 114, in forward
    return F.linear(input, self.weight, self.bias)

RuntimeError: mat1 and mat2 shapes cannot be multiplied (1536x23 and 22x32)
```



### Who can help?

_No response_

### Information

- [x] The official example scripts
- [ ] My own modified scripts

### Tasks

- [x] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)

### Reproduction

```
from huggingface_hub import hf_hub_download
import torch
from transformers import InformerModel

file = hf_hub_download(
    repo_id="kashif/tourism-monthly-batch", filename="train-batch.pt", repo_type="dataset"
)
batch = torch.load(file)

model = InformerModel.from_pretrained("huggingface/informer-tourism-monthly")

# during training, one provides both past and future values
# as well as possible additional features
outputs = model(
    past_values=batch["past_values"],
    past_time_features=batch["past_time_features"],
    past_observed_mask=batch["past_observed_mask"],
    static_categorical_features=batch["static_categorical_features"],
    static_real_features=batch["static_real_features"],
    future_values=batch["future_values"],
    future_time_features=batch["future_time_features"],
)

last_hidden_state = outputs.last_hidden_state
```

### Expected behavior

no error, `outputs` contains model output

Comments:
cc @kashif 

thanks @sgugger having a look!

@SlimakSlimak just to test: the model works if you comment out the `static_real_features` argument to the `model`?


Hi, yes that works, thank you!

This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) are likely to be ignored.