Adding a GPU model to the compatibility database in tflite
Hi @rubber815, there is probably a way ... @impjdi, can you please take a look? Thanks. Hi @impjdi , 
I would like to know how to submit GPU model information to the compatibility database in tflite? Thanks.
### Issue type

Support

### Have you reproduced the bug with TensorFlow Nightly?

No

### Source

source

### TensorFlow version

tf2.15

### Custom code

Yes

### OS platform and distribution

_No response_

### Mobile device

_No response_

### Python version

_No response_

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current behavior?

I have a question in the "acceleration/compatibility" part in tflite.
As far as I know, Samsung mobile model "samsung_xclipse_920" (S22) information was recently added to the compatibility database to check and support the GPU delegation.
https://github.com/tensorflow/tensorflow/commit/1f3d148aba6a364fb1a271410de4e2f74e32e136

I would like to add "samsung_xclipse_940", a S24 model that was recently released officially on the market,
Are there any ways to do it? Is there anything already in progress? Or, can I upload some PRs (gpu_compatibility.bin ...) related to this manually?

### Standalone code to reproduce the issue

```shell
flatc -t --raw-binary --strict-json database.fbs -- gpu_compatibility.bin
flatc -b database.fbs gpu_compatibility.json
```


### Relevant log output

_No response_