`nvmlDeviceGetName` returns bytes, which is not JSON serializable.  This causes 
```
TypeError: Object of type bytes is not JSON serializable
```
error when `hub_utils.py` calls [save_json method](https://github.com/huggingface/optimum-benchmark/blob/65fa416fd503cfe9a2be7637ee30c70a4a1f96f1/optimum_benchmark/hub_utils.py#L45) as it contains the output from this function.
ex. 
```
bound method PushToHubMixin.to_dict of BenchmarkConfig(name='pytorch_bert', backend=PyTorchConfig(name='pytorch', version='2.4.0a0+3bcc3cddb5.nv24.7', _target_='optimum_benchmark.backends.pytorch.backend.PyTorchBackend', task='fill-mask', library='transformers', model_type='bert', model='bert-base-uncased', processor='bert-base-uncased', device='cuda', device_ids='0', seed=42, inter_op_num_threads=None, intra_op_num_threads=None, model_kwargs={}, processor_kwargs={}, no_weights=True, device_map=None, torch_dtype=None, eval_mode=True, to_bettertransformer=False, low_cpu_mem_usage=None, attn_implementation=None, cache_implementation=None, autocast_enabled=False, autocast_dtype=None, torch_compile=False, torch_compile_target='forward', torch_compile_config={}, quantization_scheme=None, quantization_config={}, deepspeed_inference=False, deepspeed_inference_config={}, peft_type=None, peft_config={}), scenario=InferenceConfig(name='inference', _target_='optimum_benchmark.scenarios.inference.scenario.InferenceScenario', iterations=10, duration=10, warmup_runs=10, input_shapes={'batch_size': 1, 'num_choices': 2, 'sequence_length': 128}, new_tokens=None, memory=True, latency=True, energy=False, forward_kwargs={}, generate_kwargs={}, call_kwargs={}), launcher=ProcessConfig(name='process', _target_='optimum_benchmark.launchers.process.launcher.ProcessLauncher', device_isolation=True, device_isolation_action='warn', numactl=False, numactl_kwargs={}, start_method='spawn'), environment={'cpu': ' AMD EPYC 7R13 Processor', 'cpu_count': 192, 'cpu_ram_mb': 781912.027136, 'system': 'Linux', 'machine': 'x86_64', 'platform': 'Linux-5.15.0-1063-aws-x86_64-with-glibc2.35', 'processor': 'x86_64', 'python_version': '3.10.12', 'gpu': [b'NVIDIA L4', b'NVIDIA L4', b'NVIDIA L4', b'NVIDIA L4', b'NVIDIA L4', b'NVIDIA L4', b'NVIDIA L4', b'NVIDIA L4'], 'gpu_count': 8, 'gpu_vram_mb': 193223196672, 'optimum_benchmark_version': '0.4.0', 'optimum_benchmark_commit': None, 'transformers_version': '4.43.3', 'transformers_commit': None, 'accelerate_version': '0.33.0', 'accelerate_commit': None, 'diffusers_version': None, 'diffusers_commit': None, 'optimum_version': None, 'optimum_commit': None, 'timm_version': None, 'timm_commit': None, 'peft_version': None, 'peft_commit': None})>
```
I believe that the issue can be avoided simply by decoding the bytes into string as shown in the following example.

```python
from json import dump, load
import pynvml

# Proposed version
gpus = []
pynvml.nvmlInit()
for i in range(pynvml.nvmlDeviceGetCount()):
    handle = pynvml.nvmlDeviceGetHandleByIndex(i)
    gpus.append(pynvml.nvmlDeviceGetName(handle).decode("utf-8"))
pynvml.nvmlShutdown()
data = {'gpu': gpus}

with open("/tmp/tmp.json", "w") as f:
    dump(data, f)
with open("/tmp/tmp.json", "r") as f: 
    print(f.read())
# {"gpu": ["NVIDIA L4", "NVIDIA L4", "NVIDIA L4", "NVIDIA L4", "NVIDIA L4", "NVIDIA L4", "NVIDIA L4", "NVIDIA L4"]}
```

```python
#Current version
# https://github.com/huggingface/optimum-benchmark/blob/65fa416fd503cfe9a2be7637ee30c70a4a1f96f1/optimum_benchmark/system_utils.py#L95
gpus = []
pynvml.nvmlInit()
for i in range(pynvml.nvmlDeviceGetCount()):
    handle = pynvml.nvmlDeviceGetHandleByIndex(i)
    gpus.append(pynvml.nvmlDeviceGetName(handle))
pynvml.nvmlShutdown()
data = {'gpu': gpus}

with open("/tmp/tmp.json", "w") as f:
    dump(data, f)

#Traceback (most recent call last):
#  File "/workspace/debug/debug-pynvml.py", line 14, in <module>
#    dump(data, f)
#  File "/usr/lib/python3.10/json/__init__.py", line 179, in dump
#    for chunk in iterable:
#  File "/usr/lib/python3.10/json/encoder.py", line 431, in _iterencode
#    yield from _iterencode_dict(o, _current_indent_level)
#  File "/usr/lib/python3.10/json/encoder.py", line 405, in _iterencode_dict
#    yield from chunks
#  File "/usr/lib/python3.10/json/encoder.py", line 325, in _iterencode_list
#    yield from chunks
#  File "/usr/lib/python3.10/json/encoder.py", line 438, in _iterencode
#    o = _default(o)
#  File "/usr/lib/python3.10/json/encoder.py", line 179, in default
#    raise TypeError(f'Object of type {o.__class__.__name__} '
#TypeError: Object of type bytes is not JSON serializable
#make: *** [Makefile:25: debug-pynvml] Error 1
```