Yash/dev llava next
https://wandb.ai/joc/llava_next_energon/runs/70551i0j?nw=nwuserykarnati - fine tuning convergence run on LLaVA dataset
# What does this PR do ?

Support training of LLaVa NeXt model.

**Collection**: [Note which collection this PR will affect]
Multimodal 
# Changelog 
- Added necessary task encoders for energon data module to support training LLaVA NeXT with NeVA Model

# Usage
The only change is to use the energon based data module as shown below with existing NeVA model


```python
from nemo.collections.multimodal.data.energon.config import MultiModalSampleConfig
from nemo.collections.vlm import LlavaNextTaskEncoder
from nemo.collections.multimodal.data.energon import SimpleMultiModalDataModule
from transformers import AutoProcessor
processor = AutoProcessor.from_pretrained("llava-hf/llava-v1.6-mistral-7b-hf")
    data_path = args.data_path
    image_processor = processor.image_processor
    tokenizer = processor.tokenizer

    multimodal_sample_config = MultiModalSampleConfig()

    task_encoder = LlavaNextTaskEncoder(
        tokenizer=tokenizer, image_processor=image_processor, multimodal_sample_config=multimodal_sample_config
    )
    data = SimpleMultiModalDataModule(
        path=data_path,
        tokenizer=tokenizer,
        image_processor=image_processor,
        num_workers=8,
        micro_batch_size=mbs,
        global_batch_size=gbs,
        multimodal_sample_config=multimodal_sample_config,
        task_encoder=task_encoder,
    )
```

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# Additional Information
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