Not able to run LLaVA-Next pretraining with NeMo 2.0 using container version nemo:24.12
At step 7 when we got the error

```
AttributeError: 'MockDataModule' object has no attribute 'micro_batch_size'
```

could this be a similar issue to this [stackoverflow question](https://stackoverflow.com/questions/1250103/attributeerror-module-object-has-no-attribute), where some dependency imports are messed up? Hello, Sorry for the inconvenience. This particular PR [11424](https://github.com/NVIDIA/NeMo/pull/11424/) was missed by our cherrypicking process into release branch. While we are actively working on fixing that,  could you try with ToT [main](https://github.com/NVIDIA/NeMo/tree/main). Thank you! https://github.com/NVIDIA/NeMo/pull/11783

We would be releasing a new container with the fixes soon. 
**Describe the bug**

I would love to run LLaVA-Next pretraining with NeMo 2.0 following the [documentation](https://docs.nvidia.com/nemo-framework/user-guide/latest/vlms/llavanext.html) but failed with various errors with either nemo:24.12, nemo:24.09 or nemo:dev.

**Steps/Code to reproduce bug**

1. Pull the latest NeMo container version:
```bash
docker pull nvcr.io/nvidia/nemo:24.12
```

2. Start the docker container:
```bash
docker run --gpus all -it --rm --shm-size=32g -p 8888:8888 -p 6006:6006 --ulimit memlock=-1 --ulimit stack=67108864 nvcr.io/nvidia/nemo:24.12
```

3. Within the docker container, create the Python code `pretrain.py` and fill with the [sample code from the documentation](https://docs.nvidia.com/nemo-framework/user-guide/latest/vlms/llavanext.html):
```python
from nemo.collections import vlm

finetune = vlm.llava_next_7b.pretrain_recipe(
    name="llava_next_7b_pretrain",
    dir=f"/NeMo/new-ckpts",
    num_nodes=1,
    num_gpus_per_node=8,
    language_model_from_pretrained='/NeMo/neva/checkpoints/llama-3-8b-instruct.nemo', # This is the directory where I transformed the Llama3-8b-Instruct checkpoint to .nemo format
    # Can be None or change based on local checkpoint path
)

import nemo_run as run

run.run(finetune, executor=run.LocalExecutor())
```

4. Run the code
```bash
python3 pretrain.py
```

5. Got error
```
TypeError: pretrain_recipe() got an unexpected keyword argument 'language_model_from_pretrained'
```

6. Confirmed from the code path `/opt/NeMo/nemo/collections/vlm/recipes/llava_next_7b.py` that the code does not support `language_model_from_pretrained`.
7. Removed the line that specified `language_model_from_pretrained` and tried again. Got error
```
AttributeError: 'MockDataModule' object has no attribute 'micro_batch_size'
```
8. Also tried container versions `nemo:dev` and `nemo:24.09`. Failed with errors.
```
AttributeError: module 'nemo.collections.vlm' has no attribute 'llava_next_7b'
```
Confirmed from code path that the recipes do not exist yet in those versions.

**Expected behavior**

I should be able to follow the public documentation to get the LLaVA-NEXT pretraining run just fine.

**Environment overview (please complete the following information)**

 - Environment location: GCP.
 - Method of NeMo install: Docker.
 - If method of install is [Docker], provide `docker pull` & `docker run` commands used: see above.

**Environment details**

N/A.

**Additional context**

N/A.