diff --git a/neural_compressor/torch/algorithms/fp8_quant/_quant_common/quant_config.py b/neural_compressor/torch/algorithms/fp8_quant/_quant_common/quant_config.py
index 1cf343e1a22..b64146a75db 100644
--- a/neural_compressor/torch/algorithms/fp8_quant/_quant_common/quant_config.py
+++ b/neural_compressor/torch/algorithms/fp8_quant/_quant_common/quant_config.py
@@ -44,6 +44,14 @@ class MeasureExclude(Flag):
     PARAMS = auto()
     ALL = auto()
 
+class SupportedFp8(Enum):
+    E4M3 = torch.float8_e4m3fn
+    E5M2 = torch.float8_e5m2
+
+class HpDtype(Enum):
+    BF16 = torch.bfloat16
+    FP16 = torch.float16
+    FP32 = torch.float32
 
 class ScaleMethod(Enum):
     MAX = 1
@@ -69,6 +77,13 @@ def set_hqt_config(mod, config):
     mod.__hqt_config__ = config
 
 
+def _get_enum_from_string(EnumClass, str, key):
+    if not hasattr(EnumClass, str.upper()):
+        raise ValueError(
+            f"Invalid '{key}' value in custom config ('{str}'). Enter one of {[m.name for m in EnumClass]}")
+    return EnumClass[str.upper()]
+
+
 @dataclass
 class Fp8cfg:
     cfg: Mapping[str, Any]
@@ -84,7 +99,7 @@ def parse(custom_config: Mapping[str, str]) -> Fp8cfg:
             },  # types and names to not be quantized
             "allowlist": {
                 "names": [],
-                "types": ("torch.nn.Linear", "torch.nn.Conv2d", "BMM"),
+                "types": (),
             },  # types and names to be quantized. Allowlist by names is not yet implemented
             "mode": QuantMode.QUANTIZE,  # Quantize or Measure
             "scale_method": ScaleMethod.UNIT_SCALE,  # Method to quantize with
@@ -104,79 +119,19 @@ def parse(custom_config: Mapping[str, str]) -> Fp8cfg:
         # go over all user-defined keys from json, handle various cases
         for keys in custom_config:
             if keys == "mode":
-                if custom_config[keys] == "NONE":
-                    custom_config[keys] = QuantMode.NONE
-                elif custom_config[keys] == "QUANTIZE":
-                    custom_config[keys] = QuantMode.QUANTIZE
-                elif custom_config[keys] == "MEASURE":
-                    custom_config[keys] = QuantMode.MEASURE
-                elif custom_config[keys] == "SHAPE":
-                    custom_config[keys] = QuantMode.SHAPE
-                else:
-                    raise ValueError("invalid mode in custom config. Enter Quantize or Measure")
+                custom_config[keys] = _get_enum_from_string(QuantMode, custom_config[keys], keys)
 
             if keys == "measure_exclude":
-                if custom_config[keys] == "NONE":
-                    custom_config[keys] = MeasureExclude.NONE
-                elif custom_config[keys] == "OUTPUT":
-                    custom_config[keys] = MeasureExclude.OUTPUT
-                elif custom_config[keys] == "INPUT":
-                    custom_config[keys] = MeasureExclude.INPUT
-                elif custom_config[keys] == "ALL":
-                    custom_config[keys] = MeasureExclude.ALL
-                else:
-                    raise ValueError("invalid measure exclude value in custom config. Enter OUTPUT or NONE")
+                custom_config[keys] = _get_enum_from_string(MeasureExclude, custom_config[keys], keys)
 
             if keys == "fp8_config":
-                if custom_config[keys].lower() == "e4m3":
-                    custom_config[keys] = torch.float8_e4m3fn
-
-                elif custom_config[keys].lower() == "e5m2":
-                    custom_config[keys] = torch.float8_e5m2
-                else:
-                    raise ValueError("invalid fp8_config in custom config. Enter E4M3 or E5M2")
+                custom_config[keys] = _get_enum_from_string(SupportedFp8, custom_config[keys], keys).value
 
             if keys == "hp_dtype":
-                if custom_config[keys].lower() == "bf16":
-                    custom_config[keys] = torch.bfloat16
-                elif custom_config[keys].lower() == "fp16":
-                    custom_config[keys] = torch.float16
-                elif custom_config[keys].lower() == "fp32":
-                    custom_config[keys] = torch.float32
-                else:
-                    raise ValueError("invalid hp_dtype in custom config. Enter bf16, fp16 or fp32")
+                custom_config[keys] = _get_enum_from_string(HpDtype, custom_config[keys], keys).value
 
             if keys == "scale_method":
-                if custom_config[keys].lower() == "unit_scale":
-                    custom_config[keys] = ScaleMethod.UNIT_SCALE
-                elif custom_config[keys].lower() == "max":
-                    custom_config[keys] = ScaleMethod.MAX
-                elif custom_config[keys].lower() == "maxabs_hw":
-                    custom_config[keys] = ScaleMethod.MAXABS_HW
-                elif custom_config[keys].lower() == "maxabs_pow2":
-                    custom_config[keys] = ScaleMethod.MAXABS_POW2
-                elif custom_config[keys].lower() == "maxabs_hw_opt_weight":
-                    custom_config[keys] = ScaleMethod.MAXABS_HW_OPT_WEIGHT
-                elif custom_config[keys].lower() == "maxabs_pow2_opt_weight":
-                    custom_config[keys] = ScaleMethod.MAXABS_POW2_OPT_WEIGHT
-                elif custom_config[keys].lower() == "smoothquant_weights_output_channel_maxabs_pow2":
-                    custom_config[keys] = ScaleMethod.SMOOTHQUANT_WEIGHTS_OUTPUT_CHANNEL_MAXABS_POW2
-                elif custom_config[keys].lower() == "weaksmoothquant_weights_output_channel_maxabs_pow2":
-                    custom_config[keys] = ScaleMethod.WEAKSMOOTHQUANT_WEIGHTS_OUTPUT_CHANNEL_MAXABS_POW2
-                elif custom_config[keys].lower() == "act_maxabs_hw_weights_pcs_maxabs_pow2":
-                    custom_config[keys] = ScaleMethod.ACT_MAXABS_HW_WEIGHTS_PCS_MAXABS_POW2
-                elif custom_config[keys].lower() == "act_maxabs_hw_weights_pcs_opt_pow2":
-                    custom_config[keys] = ScaleMethod.ACT_MAXABS_HW_WEIGHTS_PCS_OPT_POW2
-                elif custom_config[keys].lower() == "act_maxabs_pow2_weights_pcs_maxabs_pow2":
-                    custom_config[keys] = ScaleMethod.ACT_MAXABS_POW2_WEIGHTS_PCS_MAXABS_POW2
-                elif custom_config[keys].lower() == "act_maxabs_pow2_weights_pcs_opt_pow2":
-                    custom_config[keys] = ScaleMethod.ACT_MAXABS_POW2_WEIGHTS_PCS_OPT_POW2
-                elif custom_config[keys].lower() == "smoothquant_opt":
-                    custom_config[keys] = ScaleMethod.SMOOTHQUANT_OPT
-                else:
-                    raise ValueError(
-                        f'Invalid fp8_config in custom config ({custom_config[keys]}). should be in ["max", "unit_scale", "maxabs_hw", "maxabs_pow2", "maxabs_per_channel_pow2", "smoothquant_opt"]'
-                    )
+                custom_config[keys] = _get_enum_from_string(ScaleMethod, custom_config[keys], keys)
 
             if keys == "ignore_modules_wo_measures":
                 custom_config[keys] = custom_config[keys].lower() == "true"