Husnain
commited on
💥 [Fix] Revert chat templates with mannual version as nous-mixtral-8x…
Browse files- messagers/message_composer.py +26 -129
messagers/message_composer.py
CHANGED
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@@ -1,23 +1,19 @@
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import re
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from pprint import pprint
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from utils.logger import logger
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class MessageComposer:
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# LINK - apis/chat_api.py#available-models
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AVALAIBLE_MODELS = [
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"mixtral-8x7b",
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"mistral-7b",
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"openchat-3.5",
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"nous-mixtral-8x7b",
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"gemma-7b",
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]
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def __init__(self, model: str = None):
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if model in
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self.model = model
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else:
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self.model = "mixtral-8x7b"
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self.system_roles = ["system"]
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self.inst_roles = ["user", "system", "inst"]
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self.answer_roles = ["assistant", "bot", "answer", "model"]
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@@ -51,12 +47,16 @@ class MessageComposer:
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return concat_messages
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def merge(self, messages) -> str:
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# Mistral and Mixtral:
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# <s> [INST] Instruction [/INST] Model answer </s> [INST] Follow-up instruction [/INST]
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# OpenChat:
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# GPT4 Correct User: Hello<|end_of_turn|>GPT4 Correct Assistant: Hi<|end_of_turn|>GPT4 Correct User: How are you today?<|end_of_turn|>GPT4 Correct Assistant:
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# Nous Mixtral:
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# <|im_start|>system
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# You are "Hermes 2".<|im_end|>
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@@ -64,6 +64,9 @@ class MessageComposer:
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# Hello, who are you?<|im_end|>
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# <|im_start|>assistant
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# Google Gemma-it
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# <start_of_turn>user
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# How does the brain work?<end_of_turn>
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@@ -145,127 +148,23 @@ class MessageComposer:
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)
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self.merged_str_list.append(f"{self.start_of_turn}model\n")
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self.merged_str = "\n".join(self.merged_str_list)
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else:
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for message in self.messages
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]
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)
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return self.merged_str
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def convert_pair_matches_to_messages(self, pair_matches_list):
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messages = []
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if len(pair_matches_list) <= 0:
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messages = [
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{
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"role": "user",
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"content": self.merged_str,
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}
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]
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else:
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for match in pair_matches_list:
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inst = match.group("inst")
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answer = match.group("answer")
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messages.extend(
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[
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{"role": "user", "content": inst.strip()},
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{"role": "assistant", "content": answer.strip()},
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]
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)
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return messages
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def append_last_instruction_to_messages(self, inst_matches_list, pair_matches_list):
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if len(inst_matches_list) > len(pair_matches_list):
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self.messages.extend(
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[
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{
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"role": "user",
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"content": inst_matches_list[-1].group("inst").strip(),
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}
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]
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)
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def split(self, merged_str) -> list:
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self.merged_str = merged_str
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self.messages = []
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if self.model in ["mixtral-8x7b", "mistral-7b"]:
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pair_pattern = (
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r"<s>\s*\[INST\](?P<inst>[\s\S]*?)\[/INST\](?P<answer>[\s\S]*?)</s>"
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)
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pair_matches = re.finditer(pair_pattern, self.merged_str, re.MULTILINE)
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pair_matches_list = list(pair_matches)
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self.messages = self.convert_pair_matches_to_messages(pair_matches_list)
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inst_pattern = r"\[INST\](?P<inst>[\s\S]*?)\[/INST\]"
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inst_matches = re.finditer(inst_pattern, self.merged_str, re.MULTILINE)
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inst_matches_list = list(inst_matches)
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self.append_last_instruction_to_messages(
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inst_matches_list, pair_matches_list
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)
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elif self.model in ["nous-mixtral-8x7b"]:
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# https://huggingface.co/NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO#prompt-format
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# message_pattern = r"<\|im_start\|>(?P<role>system|user|assistant)[\s\n]*(?P<content>[\s\S]*?)<\|im_end\|>"
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message_pattern = r"<\|im_start\|>(?P<role>system|user|assistant)[\s\n]*(?P<content>[\s\S]*?)<\|im_end\|>"
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message_matches = re.finditer(
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message_pattern, self.merged_str, flags=re.MULTILINE | re.IGNORECASE
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)
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message_matches_list = list(message_matches)
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logger.note(f"message_matches_list: {message_matches_list}")
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for match in message_matches_list:
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role = match.group("role")
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content = match.group("content")
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self.messages.append({"role": role, "content": content.strip()})
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elif self.model in ["openchat-3.5"]:
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pair_pattern = r"GPT4 Correct User:(?P<inst>[\s\S]*?)<\|end_of_turn\|>\s*GPT4 Correct Assistant:(?P<answer>[\s\S]*?)<\|end_of_turn\|>"
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pair_matches = re.finditer(
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pair_pattern, self.merged_str, flags=re.MULTILINE | re.IGNORECASE
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)
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pair_matches_list = list(pair_matches)
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self.messages = self.convert_pair_matches_to_messages(pair_matches_list)
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inst_pattern = r"GPT4 Correct User:(?P<inst>[\s\S]*?)<\|end_of_turn\|>"
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inst_matches = re.finditer(
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inst_pattern, self.merged_str, flags=re.MULTILINE | re.IGNORECASE
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)
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inst_matches_list = list(inst_matches)
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self.append_last_instruction_to_messages(
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inst_matches_list, pair_matches_list
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)
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# https://huggingface.co/google/gemma-7b-it#chat-template
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elif self.model in ["gemma-7b"]:
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pair_pattern = r"<start_of_turn>user[\s\n]*(?P<inst>[\s\S]*?)<end_of_turn>[\s\n]*<start_of_turn>model(?P<answer>[\s\S]*?)<end_of_turn>"
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pair_matches = re.finditer(
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pair_pattern, self.merged_str, flags=re.MULTILINE | re.IGNORECASE
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)
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pair_matches_list = list(pair_matches)
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self.messages = self.convert_pair_matches_to_messages(pair_matches_list)
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inst_pattern = r"<start_of_turn>user\n(?P<inst>[\s\S]*?)<end_of_turn>"
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inst_matches = re.finditer(
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inst_pattern, self.merged_str, flags=re.MULTILINE | re.IGNORECASE
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)
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inst_matches_list = list(inst_matches)
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self.append_last_instruction_to_messages(
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inst_matches_list, pair_matches_list
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)
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else:
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self.messages = [
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{
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"role": "user",
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"content": self.merged_str,
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}
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]
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return self.messages
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if __name__ == "__main__":
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# model = "mixtral-8x7b"
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# model = "nous-mixtral-8x7b"
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model = "gemma-7b"
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composer = MessageComposer(model)
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messages = [
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{
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merged_str = composer.merge(messages)
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logger.note("merged_str:")
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logger.mesg(merged_str)
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# logger.note("merged merged_str:")
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# logger.mesg(composer.merge(composer.split(merged_str)))
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import re
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from pprint import pprint
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from transformers import AutoTokenizer
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from constants.models import AVAILABLE_MODELS, MODEL_MAP
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from utils.logger import logger
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class MessageComposer:
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def __init__(self, model: str = None):
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if model in AVAILABLE_MODELS:
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self.model = model
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else:
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self.model = "mixtral-8x7b"
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self.model_fullname = MODEL_MAP[self.model]
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self.system_roles = ["system"]
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self.inst_roles = ["user", "system", "inst"]
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self.answer_roles = ["assistant", "bot", "answer", "model"]
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return concat_messages
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def merge(self, messages) -> str:
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# Templates for Chat Models
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# - https://huggingface.co/docs/transformers/main/en/chat_templating
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# - https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1#instruction-format
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# - https://huggingface.co/NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO#prompt-format
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# - https://huggingface.co/openchat/openchat-3.5-0106
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# - https://huggingface.co/google/gemma-7b-it#chat-template
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# Mistral and Mixtral:
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# <s> [INST] Instruction [/INST] Model answer </s> [INST] Follow-up instruction [/INST]
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# Nous Mixtral:
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# <|im_start|>system
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# You are "Hermes 2".<|im_end|>
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# Hello, who are you?<|im_end|>
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# <|im_start|>assistant
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# OpenChat:
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# GPT4 Correct User: Hello<|end_of_turn|>GPT4 Correct Assistant: Hi<|end_of_turn|>GPT4 Correct User: How are you today?<|end_of_turn|>GPT4 Correct Assistant:
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# Google Gemma-it
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# <start_of_turn>user
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# How does the brain work?<end_of_turn>
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)
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self.merged_str_list.append(f"{self.start_of_turn}model\n")
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self.merged_str = "\n".join(self.merged_str_list)
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# https://huggingface.co/NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO#prompt-format
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# https://huggingface.co/openchat/openchat-3.5-0106
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# elif self.model in ["openchat-3.5", "nous-mixtral-8x7b"]:
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else:
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tokenizer = AutoTokenizer.from_pretrained("openchat/openchat-3.5-0106")
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self.merged_str = tokenizer.apply_chat_template(
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messages, tokenize=False, add_generation_prompt=True
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)
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return self.merged_str
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if __name__ == "__main__":
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# model = "mixtral-8x7b"
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# model = "nous-mixtral-8x7b"
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# model = "gemma-7b"
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model = "openchat-3.5"
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composer = MessageComposer(model)
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messages = [
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{
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merged_str = composer.merge(messages)
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logger.note("merged_str:")
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logger.mesg(merged_str)
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# python -m messagers.message_composer
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