make inference server load checkpoints for fp8 inference

- introduce quantization related args for inference config
- also kill GeneratorArgs

toolchain/inference/quantization/model.py

@@ -18,6 +18,12 @@ from fp8.fp8_impls import ffn_swiglu
 from torch import nn
 
 
+@dataclass
+class QuantizationArgs:
+    fp8_rowwise: bool = False
+    convert_from_bf16: bool = False
+
+
 @dataclass
 class ModelArgs:
     dim: int = 4096
@@ -31,6 +37,8 @@ class ModelArgs:
     rope_theta: float = 500000
     use_scaled_rope: bool = False
 
+    quantization: Optional[QuantizationArgs] = None
+
     max_batch_size: int = 32
     max_seq_len: int = 2048