Model parameters size is zero when using fabric.sharded_model() context with deepspeed zero-3 strategy

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### Bug description

Hi,

I use fabric with deepspeed zero-3 strategy to shard model among 2 gpus, and get ```Model params = 0.0 M``` of model size when using with fabric.sharded_model() context.

```Python
import lightning as L

fabric = L.Fabric(accelerator="cuda", strategy='deepspeed_stage_3', precision='bf16-mixed')
fabric.launch()

with fabric.sharded_model():
net = mymodel()
num_params = sum([param.nelement() for param in net.parameters()])
fabric.print('Model params = %2.1f M' % (num_params / 1000**2))
```

Without the fabric.sharded_model() context, I get the correct model size as ```Model params = 13.6 M```.
How to solve this issue? Thanks.

### What version are you seeing the problem on?

v2.0

### How to reproduce the bug

_No response_

### Error messages and logs

```
# Error messages and logs here please
```

### Environment

Current environment

```
#- Lightning Component (e.g. Trainer, LightningModule, LightningApp, LightningWork, LightningFlow):
#- PyTorch Lightning Version (e.g., 1.5.0):
#- Lightning App Version (e.g., 0.5.2):
#- PyTorch Version (e.g., 2.0):
#- Python version (e.g., 3.9):
#- OS (e.g., Linux):
#- CUDA/cuDNN version:
#- GPU models and configuration:
#- How you installed Lightning(`conda`, `pip`, source):
#- Running environment of LightningApp (e.g. local, cloud):
```

### More info

_No response_

cc @carmocca @justusschock @awaelchli

Start at the fabric.sharded_model() entry point and the deepspeed_stage_3 strategy, then reproduce the provided two-GPU example and compare parameter counts inside and outside the context. Done means the sharded-model path reports the correct nonzero model size, with a regression test covering the behavior.

Written by the indexing model from the issue text.