Support CodeLlama model in NeuralChat (#711)

* Support neural-chat-7b-v3 and neural-chat-7b-v3-1

Signed-off-by: lvliang-intel <liang1.lv@intel.com>

Author: lvliang-intel

intel_extension_for_transformers/neural_chat/chatbot.py

@@ -72,7 +72,7 @@ def build_chatbot(config: PipelineConfig=None):
         adapter = BaseModel()
     else:
         raise ValueError("NeuralChat Error: Unsupported model name or path, \
-                         only supports FLAN-T5/LLAMA/MPT/GPT/BLOOM/OPT/QWEN/NEURAL-CHAT/MISTRAL now.")
+           only supports FLAN-T5/LLAMA/MPT/GPT/BLOOM/OPT/QWEN/NEURAL-CHAT/MISTRAL/CODELLAMA/STARCODER now.")
 
     # register plugin instance in model adaptor
     if config.plugins:

intel_extension_for_transformers/neural_chat/models/base_model.py

@@ -145,7 +145,7 @@ def predict_stream(self, query, config=None):
         query_include_prompt = False
         self.get_conv_template(self.model_name, config.task)
         if (self.conv_template.roles[0] in query and self.conv_template.roles[1] in query) or \
-              "starcoder" in self.model_name:
+              "starcoder" in self.model_name or "codellama" in self.model_name.lower():
             query_include_prompt = True
 
         # plugin pre actions
@@ -220,7 +220,7 @@ def predict(self, query, config=None):
         query_include_prompt = False
         self.get_conv_template(self.model_name, config.task)
         if (self.conv_template.roles[0] in query and self.conv_template.roles[1] in query) or \
-               "starcoder" in self.model_name:
+               "starcoder" in self.model_name or "codellama" in self.model_name.lower():
             query_include_prompt = True
 
         # plugin pre actions

intel_extension_for_transformers/neural_chat/models/model_utils.py

@@ -365,6 +365,7 @@ def load_model(
         or re.search("neural-chat-7b-v3", model_name, re.IGNORECASE)
         or re.search("qwen", model_name, re.IGNORECASE)
         or re.search("starcoder", model_name, re.IGNORECASE)
+        or re.search("codellama", model_name, re.IGNORECASE)
         or re.search("Mistral", model_name, re.IGNORECASE)
     ) and not ipex_int8) or re.search("opt", model_name, re.IGNORECASE):
         with smart_context_manager(use_deepspeed=use_deepspeed):
@@ -377,6 +378,7 @@ def load_model(
             )
     elif (
             (re.search("starcoder", model_name, re.IGNORECASE)
+             or re.search("codellama", model_name, re.IGNORECASE)
             ) and ipex_int8
         ):
             with smart_context_manager(use_deepspeed=use_deepspeed):
@@ -389,7 +391,7 @@ def load_model(
     else:
         raise ValueError(
             f"Unsupported model {model_name}, only supports "
-            "FLAN-T5/LLAMA/MPT/GPT/BLOOM/OPT/QWEN/NEURAL-CHAT/MISTRAL now."
+            "FLAN-T5/LLAMA/MPT/GPT/BLOOM/OPT/QWEN/NEURAL-CHAT/MISTRAL/CODELLAMA/STARCODER now."
         )
 
     if re.search("llama", model.config.architectures[0], re.IGNORECASE):

intel_extension_for_transformers/neural_chat/tests/nightly/models/test_model.py

@@ -144,5 +144,33 @@ def test_get_default_conv_template_v3_1(self):
         print(result)
         self.assertIn('The Intel Xeon Scalable Processors', str(result))
 
+class TestStarCoderModel(unittest.TestCase):
+    def setUp(self):
+        return super().setUp()
+
+    def tearDown(self) -> None:
+        return super().tearDown()
+
+    def test_code_gen(self):
+        config = PipelineConfig(model_name_or_path="bigcode/starcoder")
+        chatbot = build_chatbot(config=config)
+        result = chatbot.predict("def print_hello_world():")
+        print(result)
+        self.assertIn("""print('Hello World')""", str(result))
+
+class TestCodeLlamaModel(unittest.TestCase):
+    def setUp(self):
+        return super().setUp()
+
+    def tearDown(self) -> None:
+        return super().tearDown()
+
+    def test_code_gen(self):
+        config = PipelineConfig(model_name_or_path="codellama/CodeLlama-7b-hf")
+        chatbot = build_chatbot(config=config)
+        result = chatbot.predict("def print_hello_world():")
+        print(result)
+        self.assertIn("""print('Hello World')""", str(result))
+
 if __name__ == "__main__":
     unittest.main()