diff --git a/litellm/proxy/_super_secret_config.yaml b/litellm/proxy/_super_secret_config.yaml
index eb725656a..73107ca70 100644
--- a/litellm/proxy/_super_secret_config.yaml
+++ b/litellm/proxy/_super_secret_config.yaml
@@ -1,7 +1,7 @@
 model_list:
 - model_name: claude-3-5-sonnet
   litellm_params:
-    model: anthropic/claude-3-5-sonnet
+    model: claude-3-haiku-20240307
 # - model_name: gemini-1.5-flash-gemini
 #   litellm_params:
 #     model: vertex_ai_beta/gemini-1.5-flash
diff --git a/litellm/utils.py b/litellm/utils.py
index a5f11937b..5bddae138 100644
--- a/litellm/utils.py
+++ b/litellm/utils.py
@@ -8786,11 +8786,11 @@ class CustomStreamWrapper:
             # return this for all models
             completion_obj = {"content": ""}
             if self.custom_llm_provider and self.custom_llm_provider == "anthropic":
-                from litellm.types.llms.bedrock import GenericStreamingChunk
+                from litellm.types.utils import GenericStreamingChunk as GChunk
 
                 if self.received_finish_reason is not None:
                     raise StopIteration
-                response_obj: GenericStreamingChunk = chunk
+                response_obj: GChunk = chunk
                 completion_obj["content"] = response_obj["text"]
                 if response_obj["is_finished"]:
                     self.received_finish_reason = response_obj["finish_reason"]
@@ -8802,9 +8802,9 @@ class CustomStreamWrapper:
                 ):
                     self.sent_stream_usage = True
                     model_response.usage = litellm.Usage(
-                        prompt_tokens=response_obj["usage"]["inputTokens"],
-                        completion_tokens=response_obj["usage"]["outputTokens"],
-                        total_tokens=response_obj["usage"]["totalTokens"],
+                        prompt_tokens=response_obj["usage"]["prompt_tokens"],
+                        completion_tokens=response_obj["usage"]["completion_tokens"],
+                        total_tokens=response_obj["usage"]["total_tokens"],
                     )
 
                 if "tool_use" in response_obj and response_obj["tool_use"] is not None: