[Model] Add llava mlp converter and update three models config

[Caozhou1995]

This PR adds mlp ckpt conversation from hf to megatron in the llava pretrain phase. An tp2 example of the ckpt conversation for the LLaVA Pretrain phase is shown below:

• CLIP cd FlagScale/megatron && python examples/multimodal/clip_converter.py --download-root <clip_hf_dir> --output <clip_megatron_dir> --tensor-parallel-size 2 --use-te-layernorm-linear

• Vicuna cd FlagScale/megatron && python tools/checkpoint/convert.py --model-type GPT --loader llama_mistral --saver mcore --target-tensor-parallel-size 2 --checkpoint-type hf --load-dir <vicuna_hf_dir> --save-dir <vicuna_megatron_dir> --tokenizer-model <vicuna_hf_dir>/tokenizer.model --bf16 --model-size llama2-7Bf --true-vocab-size 32256 --megatron-path <flagscale_dir>

• MLP cd FlagScale/megatron && python examples/multimodal/mlp_converter.py --input <mlp_hf_dir>/mm_projector.bin --output <mlp_megatron_dir> --tensor-parallel-size 2

And combine them: cd FlagScale/megatron && PYTHONPATH=FlagScale/megatron:FlagScale/ python examples/multimodal/combine_state_dicts.py --input <vicuna_megatron_dir>/iter_0000001/mp_rank_00/model_optim_rng.pt <clip_megatron_dir>/state_dict_tp_0.pt <mlp_megatron_dir>/state_dict_tp_0.pt <vicuna_megatron_dir>/iter_0000001/mp_rank_01/model_optim_rng.pt <clip_megatron_dir>/state_dict_tp_1.pt <mlp_megatron_dir>/state_dict_tp_1.pt --prefixes language_model vision_model vision_projection language_model vision_model vision_projection --output <output_dir>/iter_0000001/mp_rank_00/model_optim_rng.pt <output_dir>/iter_0000001/mp_rank_01/model_optim_rng.pt && cd <output_idr> && echo "1" > latest_checkpointed_iteration.txt

This PR also updates three models config.