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💎 [Feature] New model supported: zephyr-orpo-141b (HuggingFaceH4/zephyr-orpo-141b-A35b-v0.1)
Browse files- messagers/message_composer.py +15 -15
messagers/message_composer.py
CHANGED
@@ -48,10 +48,10 @@ class MessageComposer:
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def merge(self, messages) -> str:
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# Templates for Chat Models
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#
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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/
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# - https://huggingface.co/google/gemma-1.1-7b-it#chat-template
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# Mistral and Mixtral:
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@@ -64,8 +64,8 @@ class MessageComposer:
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# Hello, who are you?<|im_end|>
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# <|im_start|>assistant
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#
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#
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# Google Gemma-it
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# <start_of_turn>user
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@@ -103,8 +103,8 @@ class MessageComposer:
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self.merged_str_list.append(message_line)
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self.merged_str_list.append("<|im_start|>assistant")
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self.merged_str = "\n".join(self.merged_str_list)
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# https://huggingface.co/
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elif self.model in ["
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self.messages = self.concat_messages_by_role(messages)
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self.merged_str_list = []
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self.end_of_turn = "<|end_of_turn|>"
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@@ -113,17 +113,17 @@ class MessageComposer:
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content = message["content"]
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if role in self.inst_roles:
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self.merged_str_list.append(
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f"
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)
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elif role in self.answer_roles:
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self.merged_str_list.append(
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f"
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)
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else:
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self.merged_str_list.append(
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f"
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)
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self.merged_str_list.append(f"
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self.merged_str = "\n".join(self.merged_str_list)
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# https://huggingface.co/google/gemma-1.1-7b-it#chat-template
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elif self.model in ["gemma-1.1-7b"]:
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@@ -149,9 +149,9 @@ class MessageComposer:
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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/
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# elif self.model in ["
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elif self.model in ["
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tokenizer = AutoTokenizer.from_pretrained(self.model_fullname)
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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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@@ -168,13 +168,13 @@ if __name__ == "__main__":
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# model = "mixtral-8x7b"
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# model = "nous-mixtral-8x7b"
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# model = "gemma-1.1-7b"
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# model = "
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model = "command-r-plus"
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composer = MessageComposer(model)
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messages = [
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{
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"role": "system",
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"content": "You are
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},
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{"role": "user", "content": "Hello, who are you?"},
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{"role": "assistant", "content": "I am a bot."},
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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/HuggingFaceH4/zephyr-orpo-141b-A35b-v0.1
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# - https://huggingface.co/google/gemma-1.1-7b-it#chat-template
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# Mistral and Mixtral:
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# Hello, who are you?<|im_end|>
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# <|im_start|>assistant
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# HuggingFaceH4:
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# zephyr-orpo-141b Correct User: Hello<|end_of_turn|>zephyr-orpo-141b Correct Assistant: Hi<|end_of_turn|>zephyr-orpo-141b Correct User: How are you today?<|end_of_turn|>zephyr-orpo-141b Correct Assistant:
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# Google Gemma-it
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# <start_of_turn>user
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self.merged_str_list.append(message_line)
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self.merged_str_list.append("<|im_start|>assistant")
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self.merged_str = "\n".join(self.merged_str_list)
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# https://huggingface.co/HuggingFaceH4/zephyr-orpo-141b-A35b-v0.1
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elif self.model in ["zephyr-orpo-141b"]:
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self.messages = self.concat_messages_by_role(messages)
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self.merged_str_list = []
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self.end_of_turn = "<|end_of_turn|>"
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content = message["content"]
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if role in self.inst_roles:
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self.merged_str_list.append(
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f"zephyr-orpo-141b Correct User:\n{content}{self.end_of_turn}"
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)
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elif role in self.answer_roles:
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self.merged_str_list.append(
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f"zephyr-orpo-141b Correct Assistant:\n{content}{self.end_of_turn}"
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)
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else:
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self.merged_str_list.append(
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f"zephyr-orpo-141b Correct User: {content}{self.end_of_turn}"
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)
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self.merged_str_list.append(f"zephyr-orpo-141b Correct Assistant:\n")
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self.merged_str = "\n".join(self.merged_str_list)
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# https://huggingface.co/google/gemma-1.1-7b-it#chat-template
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elif self.model in ["gemma-1.1-7b"]:
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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/HuggingFaceH4/zephyr-orpo-141b
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# elif self.model in ["zephyr-orpo-141b", "nous-mixtral-8x7b"]:
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elif self.model in ["zephyr-orpo-141b", "command-r-plus"]:
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tokenizer = AutoTokenizer.from_pretrained(self.model_fullname)
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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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# model = "mixtral-8x7b"
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# model = "nous-mixtral-8x7b"
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# model = "gemma-1.1-7b"
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# model = "zephyr-orpo-141b"
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model = "command-r-plus"
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composer = MessageComposer(model)
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messages = [
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{
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"role": "system",
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"content": "You are Zephyr, an assistant developed by KAIST AI, Argilla, and Hugging Face. You should give concise responses to very simple questions, but provide thorough responses to more complex and open-ended questions. You are happy to help with writing, analysis, question answering, math, coding, and all sorts of other tasks.",
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},
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{"role": "user", "content": "Hello, who are you?"},
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{"role": "assistant", "content": "I am a bot."},
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