[docs] Minor fix for quantization example code (#1297)

Author: jerryzh168

docs/source/tutorials/e2e_flow.rst

@@ -327,8 +327,8 @@ To quantize the fine-tuned model after installing torchao we can run the followi
   # we also support `int8_weight_only()` and `int8_dynamic_activation_int8_weight()`, see
   # https://github.com/pytorch/ao/tree/main/torchao/quantization#other-available-quantization-techniques
   # for a full list of techniques that we support
-  from torchao.quantization.quant_api import quantize\_, int4_weight_only
-  quantize\_(model, int4_weight_only())
+  from torchao.quantization.quant_api import quantize_, int4_weight_only
+  quantize_(model, int4_weight_only())
 
 After quantization, we rely on torch.compile for speedups. For more details, please see `this example usage <https://github.com/pytorch/ao/blob/main/torchao/quantization/README.md#quantization-flow-example>`_.
 

docs/source/tutorials/llama3.rst

@@ -247,8 +247,8 @@ To quantize the fine-tuned model after installing torchao we can run the followi
   # we also support `int8_weight_only()` and `int8_dynamic_activation_int8_weight()`, see
   # https://github.com/pytorch/ao/tree/main/torchao/quantization#other-available-quantization-techniques
   # for a full list of techniques that we support
-  from torchao.quantization.quant_api import quantize\_, int4_weight_only
-  quantize\_(model, int4_weight_only())
+  from torchao.quantization.quant_api import quantize_, int4_weight_only
+  quantize_(model, int4_weight_only())
 
 After quantization, we rely on torch.compile for speedups. For more details, please see `this example usage <https://github.com/pytorch/ao/blob/main/torchao/quantization/README.md#quantization-flow-example>`_.