diff --git a/extensions/HuggingFace/python/requirements.txt b/extensions/HuggingFace/python/requirements.txt
index 6388e1c9e..79e5db10b 100644
--- a/extensions/HuggingFace/python/requirements.txt
+++ b/extensions/HuggingFace/python/requirements.txt
@@ -10,11 +10,12 @@ huggingface_hub
 
 #Hugging Face Libraries - Local Inference Tranformers & Diffusors
 accelerate # Used to help speed up image generation
-diffusers # Used for image + audio generation
+diffusers # Used for image generation
+scipy # array -> wav file, text-speech. torchaudio.save seems broken.
+sentencepiece # Used for text translation
 torch
 torchvision
 torchaudio
-scipy # array -> wav file, text-speech. torchaudio.save seems broken.
 transformers # Used for text generation
 
 #Other
diff --git a/extensions/HuggingFace/python/src/aiconfig_extension_hugging_face/local_inference/text_translation.py b/extensions/HuggingFace/python/src/aiconfig_extension_hugging_face/local_inference/text_translation.py
index 9ee8bb357..860a11e46 100644
--- a/extensions/HuggingFace/python/src/aiconfig_extension_hugging_face/local_inference/text_translation.py
+++ b/extensions/HuggingFace/python/src/aiconfig_extension_hugging_face/local_inference/text_translation.py
@@ -129,12 +129,19 @@ def construct_stream_output(
             "metadata": {},
         }
     )
+
     accumulated_message = ""
     for new_text in streamer:
         if isinstance(new_text, str):
+            # For some reason these symbols aren't filtered out by the streamer
+            new_text = new_text.replace("</s>", "")
+            new_text = new_text.replace("<s>", "")
+            new_text = new_text.replace("<pad>", "")
+
             accumulated_message += new_text
             options.stream_callback(new_text, accumulated_message, 0)
             output.data = accumulated_message
+
     return output
 
 
@@ -240,19 +247,26 @@ async def run_inference(self, prompt: Prompt, aiconfig: "AIConfigRuntime", optio
 
         model_name: str = aiconfig.get_model_name(prompt)
         if isinstance(model_name, str) and model_name not in self.translators:
-            self.translators[model_name] = pipeline(model_name)
+            self.translators[model_name] = pipeline("translation", model_name)
         translator = self.translators[model_name]
 
         # if stream enabled in runtime options and config, then stream. Otherwise don't stream.
         streamer = None
-        should_stream = (options.stream if options else False) and (not "stream" in completion_data or completion_data.get("stream") != False)
+        should_stream = (options.stream if options else False) and (
+            not "stream" in completion_data or completion_data.get("stream") != False
+        )
         if should_stream:
-            raise NotImplementedError("Streaming is not supported for HuggingFace Text Translation")
+            tokenizer: AutoTokenizer = AutoTokenizer.from_pretrained(model_name)
+            streamer = TextIteratorStreamer(tokenizer)
+            completion_data["streamer"] = streamer
+
+        def _translate():
+            return translator(inputs, **completion_data)
 
         outputs: List[Output] = []
         output = None
         if not should_stream:
-            response: List[Any] = translator(inputs, **completion_data)
+            response: List[Any] = _translate()
             for count, result in enumerate(response):
                 output = construct_regular_output(result, count)
                 outputs.append(output)
@@ -263,7 +277,7 @@ async def run_inference(self, prompt: Prompt, aiconfig: "AIConfigRuntime", optio
                 raise ValueError("Stream option is selected but streamer is not initialized")
 
             # For streaming, cannot call `translator` directly otherwise response will be blocking
-            thread = threading.Thread(target=translator, kwargs=completion_data)
+            thread = threading.Thread(target=_translate)
             thread.start()
             output = construct_stream_output(streamer, options)
             if output is not None: