AttributeError: 'MegatronGPTModel' object has no attribute 'decoder'
I'm curious if by retraining you might mean continued training? https://docs.nvidia.com/nemo-framework/user-guide/latest/llms/allmodels/continuetraining.html?highlight=continued%2520training#configure-continual-learning

Regarding your error, the decoder module will be `MegatronGPTModel.model.decoder` I believe. But you can check by inspecting the `MegatronGPTModel`  This issue is stale because it has been open for 30 days with no activity. Remove stale label or comment or this will be closed in 7 days. This issue was closed because it has been inactive for 7 days since being marked as stale.
#### Description

I am retraining a LLaMA3 model. Due to the limited size of my dataset, I attempted to use `freeze_updates` as referenced in the [NVIDIA NeMo documentation](https://docs.nvidia.com/nemo-framework/user-guide/latest/nemotoolkit/core/neural_modules.html#dynamic-layer-freezing). My configuration is as follows:

```yaml
freeze_updates:
  enabled: true  # set to false if you want to disable freezing
  modules:   # list all of the modules you want to have freezing logic for
    decoder: 100
```
However, I encountered the following error:
```
AttributeError: 'MegatronGPTModel' object has no attribute 'decoder'
```

I also tried changing decoder to `encoder` or `joint`, but I still faced errors. I would like to ask how to properly configure this setting?

Additionally, within the NeMo framework, is it possible to freeze specific layers, such as only the attention layer? If so, how can I achieve this? Thanks!