Loading loras on "text_pipe" of a modular pipeline fails

### Describe the bug

The following code works:

```python
import torch
from diffusers import Flux2Pipeline

pipe = Flux2Pipeline.from_pretrained("black-forest-labs/FLUX.2-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("flux.2-turbo-lora.safetensors")
```

but on modular it doesn't:

```python
import torch
from diffusers import ModularPipeline

pipe = ModularPipeline.from_pretrained("black-forest-labs/FLUX.2-dev")
blocks = pipe.blocks
text_blocks = blocks.sub_blocks.pop("text_encoder")
text_pipe = text_blocks.init_pipeline("black-forest-labs/FLUX.2-dev")
text_pipe.load_components(torch_dtype=torch.bfloat16)
text_pipe.load_lora_weights("flux.2-turbo-lora.safetensors")
text_pipe.set_adapters(["default"], adapter_weights=[1])
```

The lora is found here: https://huggingface.co/fal/FLUX.2-dev-Turbo/blob/main/flux.2-turbo-lora.safetensors

### Logs

```shell
src/diffusers/configuration_utils.py", line 176, in __getattr__
raise AttributeError(f"'{type(self).__name__}' object has no attribute '{name}'")
AttributeError: 'Flux2ModularPipeline' object has no attribute 'transformer'. Did you mean: 'transformer_name'?
```

### System Info

Latest commit of Diffusers 71a6fd9f0df04d3764dfa999268a05d87903a85a

### Who can help?

@yiyixuxu @DN6 @sayakpaul

Start with the ModularPipeline example using text_blocks.init_pipeline(), load_components(), load_lora_weights(), and set_adapters(). Trace the AttributeError at src/diffusers/configuration_utils.py:176 and compare this path with the working Flux2Pipeline example. Done means the modular text_pipe can load and activate the LoRA without the missing transformer attribute error.

Written by the indexing model from the issue text.