`.to` on a `PreTrainedModel` throws a Pyright type check error. What is the correct way to put a model to the device that does not throw type check errors?
Author: nickeisenberg
Pull request: no
Labels: name: bug

### System Info

(venv) nicholas@B367309:tmp(master)$ transformers-cli env

Copy-and-paste the text below in your GitHub issue and FILL OUT the two last points.

- `transformers` version: 4.51.1
- Platform: Linux-5.10.16.3-microsoft-standard-WSL2-x86_64-with-glibc2.39
- Python version: 3.12.3
- Huggingface_hub version: 0.30.2
- Safetensors version: 0.5.3
- Accelerate version: 1.6.0
- Accelerate config:    not found
- DeepSpeed version: not installed
- PyTorch version (GPU?): 2.6.0+cu126 (True)
- Tensorflow version (GPU?): not installed (NA)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using distributed or parallel set-up in script?: <fill in>
- Using GPU in script?: <fill in>
- GPU type: NVIDIA RTX 2000 Ada Generation Laptop GPU


### Who can help?

_No response_

### Information

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

### Tasks

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

### Reproduction

Here is a small snippet

```python
from transformers.models.auto.modeling_auto import AutoModelForCausalLM
from transformers.models.llama.modeling_llama import LlamaForCausalLM

model = AutoModelForCausalLM.from_pretrained(
    "deepseek-ai/deepseek-coder-1.3b-instruct", torch_dtype=torch.float16
)
assert isinstance(model, LlamaForCausalLM)
model.to("cuda:0")
```

This code runs fine and correctly puts the model to the device, however, `Pyright` throws a pre-runtime type check error on the `model.to("cuda:0") call. This is the error,

```plaintext
Pyright: Argument of type "Literal['cuda:0']" cannot be assigned to parameter "self" of 
type "LlamaForCausalLM" in function "__call__".
"Literal['cuda:0']" is not assignable to "LlamaForCausalLM" [reportArgumentType]  
```

What is the correct way to put a model to the device that will satisfy the type checker?

### Expected behavior

There should be know static type check error when doing `model.to(<device>)`

Comments:
I'm afraid we don't have complete type hint support! If you run with strict type checking, you will almost certainly encounter these errors. We recommend relaxing your typing requirements.

@Rocketknight1, how can we help with this issue? Improve type hints or what?

Hi @1himan, we do accept PRs to improve type hints, as long as they don't require library refactors! However, some of the code in Transformers (especially the code involving `Auto` classes or `dynamic_module_utils`) is intrinsically very hard to write complete and accurate types for.

I think it's a case of always improving but never being perfect!

The issue does not have to do with the `Auto` class as I am asserting that the resulting model is of type `LlamaForCausalLM`. The issue has to do with `transformers.modeling_utils.PreTrainedModel.to` as that is whats being called with `model.to` in my snippet above. I also do not have strict typing turned on, this is `Pyright` basic typing.

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.