feat: Add LLaMA-3 instruct prompt strategies for fine-tuning

src/axolotl/cli/preprocess.py

@@ -19,7 +19,10 @@
 )
 from axolotl.common.cli import PreprocessCliArgs
 from axolotl.common.const import DEFAULT_DATASET_PREPARED_PATH
-from axolotl.prompt_strategies.sharegpt import register_chatml_template
+from axolotl.prompt_strategies.sharegpt import (
+    register_chatml_template,
+    register_llama3_template,
+)
 
 LOG = logging.getLogger("axolotl.cli.preprocess")
 
@@ -36,13 +39,22 @@ def do_cli(config: Union[Path, str] = Path("examples/"), **kwargs):
         return_remaining_strings=True
     )
 
-    if parsed_cfg.chat_template == "chatml" and parsed_cfg.default_system_message:
-        LOG.info(
-            f"ChatML set. Adding default system message: {parsed_cfg.default_system_message}"
-        )
-        register_chatml_template(parsed_cfg.default_system_message)
-    else:
-        register_chatml_template()
+    if parsed_cfg.chat_template == "chatml":
+        if parsed_cfg.default_system_message:
+            LOG.info(
+                f"ChatML set. Adding default system message: {parsed_cfg.default_system_message}"
+            )
+            register_chatml_template(parsed_cfg.default_system_message)
+        else:
+            register_chatml_template()
+    elif parsed_cfg.chat_template == "llama3":
+        if parsed_cfg.default_system_message:
+            LOG.info(
+                f"LLaMA-3 set. Adding default system message: {parsed_cfg.default_system_message}"
+            )
+            register_llama3_template(parsed_cfg.default_system_message)
+        else:
+            register_llama3_template()
 
     if not parsed_cfg.dataset_prepared_path:
         msg = (

src/axolotl/cli/train.py

@@ -19,7 +19,10 @@
     print_axolotl_text_art,
 )
 from axolotl.common.cli import TrainerCliArgs
-from axolotl.prompt_strategies.sharegpt import register_chatml_template
+from axolotl.prompt_strategies.sharegpt import (
+    register_chatml_template,
+    register_llama3_template,
+)
 from axolotl.train import train
 
 LOG = logging.getLogger("axolotl.cli.train")
@@ -47,6 +50,14 @@ def do_train(cfg, cli_args) -> Tuple[PreTrainedModel, PreTrainedTokenizer]:
     else:
         register_chatml_template()
 
+    if cfg.chat_template == "llama3" and cfg.default_system_message:
+        LOG.info(
+            f"LLaMA-3 set. Adding default system message: {cfg.default_system_message}"
+        )
+        register_llama3_template(cfg.default_system_message)
+    else:
+        register_llama3_template()
+
     if cfg.rl:  # and cfg.rl != "orpo":
         dataset_meta = load_rl_datasets(cfg=cfg, cli_args=cli_args)
     else:

src/axolotl/prompt_strategies/sharegpt.py

@@ -22,7 +22,7 @@ def register_chatml_template(system_message=None):
             name="chatml",
             system_template="<|im_start|>system\n{system_message}",
             system_message=system_message,
-            roles=["<|im_start|>user", "<|im_start|>assistant"],
+            roles=("<|im_start|>user", "<|im_start|>assistant"),
             sep_style=SeparatorStyle.CHATML,
             sep="<|im_end|>",
         )
@@ -32,13 +32,29 @@ def register_chatml_template(system_message=None):
             name="chatml_glaive",
             system_template="<|im_start|>system\n{system_message}",
             system_message=system_message,
-            roles=["<|im_start|>user", "<|im_start|>assistant", "<|im_start|>tool"],
+            roles=("<|im_start|>user", "<|im_start|>assistant", "<|im_start|>tool"),
             sep_style=SeparatorStyle.CHATML,
             sep="<|im_end|>",
         )
     )
 
 
+def register_llama3_template(system_message=None):
+    system_message = system_message or "You are a helpful assistant."
+    register_conv_template(
+        Conversation(
+            name="llama3",
+            system_template="<|start_header_id|>system<|end_header_id|>\n\n{system_message}<|eot_id|>",
+            system_message=system_message,
+            roles=("user", "assistant"),
+            sep_style=SeparatorStyle.LLAMA3,
+            sep="",
+            stop_str="<|eot_id|>",
+            stop_token_ids=[128001, 128009],
+        )
+    )
+
+
 def build_loader(
     tokenization_strategy_cls: Type["ShareGPTPromptTokenizingStrategy"],
     prompter_cls: Type["ShareGPTPrompterV2"],

src/axolotl/prompters.py

@@ -263,6 +263,7 @@ def __repr__(self) -> str:
     "chatml": "<|im_start|>{ROLE}",
     "zephyr": "<|{ROLE}|>",
     "vicuna_v1.1": "{ROLE}",
+    "llama3": "<|start_header_id|>{ROLE}<|end_header_id|>",
 }
 
 

src/axolotl/utils/chat_templates.py

@@ -24,6 +24,7 @@ def chat_templates(user_choice: str):
         "chatml": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
         "gemma": "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + '\n' + message['content'] | trim + '<end_of_turn>\n' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model\n'}}{% endif %}",
         "cohere": "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% elif false == true %}{% set loop_messages = messages %}{% set system_message = 'You are Command-R, a brilliant, sophisticated, AI-assistant trained to assist human users by providing thorough responses. You are trained by Cohere.' %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{% if system_message != false %}{{ '<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>' + system_message + '<|END_OF_TURN_TOKEN|>' }}{% endif %}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% set content = message['content'] %}{% if message['role'] == 'user' %}{{ '<|START_OF_TURN_TOKEN|><|USER_TOKEN|>' + content.strip() + '<|END_OF_TURN_TOKEN|>' }}{% elif message['role'] == 'assistant' %}{{ '<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>'  + content.strip() + '<|END_OF_TURN_TOKEN|>' }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>' }}{% endif %}",
+        "llama3": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>\n\n' }}{% else %}{{ eos_token }}{% endif %}",
     }
 
     if user_choice in templates:

src/axolotl/utils/config/models/input/v0_4_1/__init__.py

@@ -143,6 +143,7 @@ class ChatTemplate(str, Enum):
     inst = "inst"  # pylint: disable=invalid-name
     gemma = "gemma"  # pylint: disable=invalid-name
     cohere = "cohere"  # pylint: disable=invalid-name
+    llama3 = "llama3"  # pylint: disable=invalid-name
 
 
 class LoftQConfig(BaseModel):

tests/prompt_strategies/test_sharegpt.py

@@ -12,10 +12,12 @@
     GlaiveShareGPTPromptTokenizingStrategy,
     SimpleShareGPTPromptTokenizingStrategy,
     register_chatml_template,
+    register_llama3_template,
 )
 from axolotl.prompters import ShareGPTPrompterV2
 
 register_chatml_template()
+register_llama3_template()
 
 
 @pytest.fixture(name="sharegpt_dataset")
@@ -115,7 +117,53 @@ def fixture_tokenizer():
     return tokenizer
 
 
-class TestSharegpt:
+@pytest.fixture(name="llama3_tokenizer")
+def fixture_llama3_tokenizer():
+    tokenizer = AutoTokenizer.from_pretrained("NousResearch/Meta-Llama-3-8B")
+    tokenizer.eos_token = "<|eot_id|>"
+
+    return tokenizer
+
+
+class TestSharegptLlama3:
+    """Test class for ShareGPT style datasets with llama-3 prompts"""
+
+    def test_tokenization(self, sharegpt_dataset, llama3_tokenizer):
+        strategy = SimpleShareGPTPromptTokenizingStrategy(
+            ShareGPTPrompterV2(
+                conversation="llama3",
+                role_key_model=None,
+                role_key_human=None,
+            ),
+            llama3_tokenizer,
+            False,  # train_on_inputs
+            2048,  # sequence_len
+        )
+
+        dataset_wrapper = TokenizedPromptDataset(
+            strategy, sharegpt_dataset, process_count=1
+        )
+
+        input_ids = dataset_wrapper[0]["input_ids"]
+
+        # fmt: off
+        assert input_ids == [
+            128000,  # bos
+            128006, 9125, 128007,  # system header
+            271, 31724, 128009,  # sys prompt, eot
+            128006, 882, 128007,  # user header
+            271, 15339, 128009,  # user prompt eot
+            128006, 78191, 128007,  # assistant header
+            271, 15339, 128009,   # assistant response eot
+            128006, 882, 128007,
+            271, 19045, 29474, 128009,
+            128006, 78191, 128007,
+            271, 19045, 29474, 128009,
+        ]
+        # fmt: on
+
+
+class TestSharegptChatML:
     """
     Test class for sharegpt prompter
     """