multigpu support for summarization ppo example

### 🐛 Describe the bug

this is not a bug. wanted to know how we can run the ppo training for summarization. this is the file i am trying to run: trlx_gptj_text_summarization.py which is in trlx/examples/summarize_rlhf. i tried to run it with changed accelerate configs:
'''
compute_environment: LOCAL_MACHINE
debug: false
deepspeed_config:
gradient_accumulation_steps: 1
gradient_clipping: 1.0
offload_optimizer_device: cpu
offload_param_device: cpu
zero3_init_flag: false
zero_stage: 2
distributed_type: DEEPSPEED
downcast_bf16: 'no'
machine_rank: 0
main_training_function: main
mixed_precision: bf16
num_machines: 1
num_processes: 8
rdzv_backend: static
same_network: true
tpu_env: []
tpu_use_cluster: false
tpu_use_sudo: false
use_cpu: false
'''

ran it with accelerate launch --config_file configs/default_accelerate_config.yaml trlx_gptj_text_summarization.py.
but got cuda out of memory.
I am using 8 x RTX6000 GPUs. 76 vCPUs and 400GB RAM.

Do i need to make changes in the trlx_gptj_text_summarization.py file as well? if yes, please tell what changes are required.
Quick resolution will be highly appreciated.

### Which trlX version are you using?

_No response_

### Additional system and package information

_No response_