Fix: LLM API logits processor example comments

examples/llm-api/llm_logits_processor.py

@@ -9,7 +9,7 @@
 
 
 # The recommended way to create a customized logits processor:
-#     * Subclass this class and implement the processing logics in the __call__ method.
+#     * Subclass LogitsProcessor and implement the processing logics in the __call__ method.
 #     * Create an instance and pass to SamplingParams.
 # Alternatively, you can create any callable with the same signature with the __call__ method.
 # This simple callback will output a specific token at each step irrespective of prompt.
@@ -32,7 +32,7 @@ def __call__(self, req_id: int, logits: torch.Tensor,
 
 
 # The recommended way to create a customized batched logits processor:
-#     * Subclass this class and implement the processing logics in the __call__ method.
+#     * Subclass BatchedLogitsProcessor and implement the processing logics in the __call__ method.
 #     * Create an instance and pass to LLM.
 # Alternatively, you can create any callable with the same signature with the __call__ method.
 # A batched logits processor's arguments for all requests in a batch are made available as lists.