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# Copyright (c) OpenMMLab. All rights reserved.
from mmengine.config import ConfigDict
# - Turn 0: SYSTEM + INSTRUCTION, [output + SUFFIX], SEP
# - Turn 1: INSTRUCTION, [output + SUFFIX], SEP
# - Turn ...
# Note: [] means having supervised loss during the fine-tuning
PROMPT_TEMPLATE = ConfigDict(
default=dict(
SYSTEM='<|System|>:{system}\n',
INSTRUCTION='<|User|>:{input}\n<|Bot|>:',
SEP='\n'),
zephyr=dict(
SYSTEM='<|system|>\n{system}\n',
INSTRUCTION='<|user|>\n{input}\n<|assistant|>\n',
SEP='\n'),
internlm_chat=dict(
SYSTEM='<|System|>:{system}\n',
INSTRUCTION='<|User|>:{input}<eoh>\n<|Bot|>:',
SUFFIX='<eoa>',
SUFFIX_AS_EOS=True,
SEP='\n',
STOP_WORDS=['<eoa>']),
internlm2_chat=dict(
SYSTEM='<|im_start|>system\n{system}<|im_end|>\n',
INSTRUCTION=('<|im_start|>user\n{input}<|im_end|>\n'
'<|im_start|>assistant\n'),
SUFFIX='<|im_end|>',
SUFFIX_AS_EOS=True,
SEP='\n',
STOP_WORDS=['<|im_end|>']),
moss_sft=dict(
SYSTEM='{system}\n',
INSTRUCTION='<|Human|>: {input}<eoh>\n',
SEP='\n',
STOP_WORDS=['<eoc>', '<eom>']),
llama2_chat=dict(
SYSTEM=(
'[INST] <<SYS>>\n You are a helpful, respectful and honest '
'assistant. Always answer as helpfully as possible, while being '
'safe. Your answers should not include any harmful, unethical, '
'racist, sexist, toxic, dangerous, or illegal content. Please '
'ensure that your responses are socially unbiased and positive in '
'nature.\n{system}\n<</SYS>>\n [/INST] '),
INSTRUCTION='[INST] {input} [/INST]',
SEP='\n'),
code_llama_chat=dict(
SYSTEM='{system}\n', INSTRUCTION='[INST] {input} [/INST]'),
chatglm2=dict(
SYSTEM='{system}\n',
INSTRUCTION='[Round {round}]\n\n问：{input}\n\n答：',
SEP='\n\n'),
chatglm3=dict(
SYSTEM='<|system|>\n{system}',
INSTRUCTION='<|user|>\n{input}<|assistant|>\n',
SEP='\n'),
qwen_chat=dict(
SYSTEM=('<|im_start|>system\n{system}<|im_end|>\n'),
INSTRUCTION=('<|im_start|>user\n{input}<|im_end|>\n'
'<|im_start|>assistant\n'),
SUFFIX='<|im_end|>',
SUFFIX_AS_EOS=True,
SEP='\n',
STOP_WORDS=['<|im_end|>', '<|endoftext|>']),
baichuan_chat=dict(
SYSTEM='{system}\n',
INSTRUCTION='<reserved_102>{input}<reserved_103>',
SEP='\n'),
baichuan2_chat=dict(
SYSTEM='{system}\n',
INSTRUCTION='<reserved_106>{input}<reserved_107>',
SEP='\n'),
wizardlm=dict(
SYSTEM=('A chat between a curious user and an artificial '
'intelligence assistant. The assistant gives '
'helpful, detailed, and polite answers to the '
'user\'s questions. {system}\n '),
INSTRUCTION=('USER: {input} ASSISTANT:'),
SEP='\n'),
wizardcoder=dict(
SYSTEM=(
'Below is an instruction that describes a task. '
'Write a response that appropriately completes the request.\n\n'
'{system}\n '),
INSTRUCTION=('### Instruction:\n{input}\n\n### Response:'),
SEP='\n\n'),
vicuna=dict(
SYSTEM=('A chat between a curious user and an artificial '
'intelligence assistant. The assistant gives '
'helpful, detailed, and polite answers to the '
'user\'s questions. {system}\n '),
INSTRUCTION=('USER: {input} ASSISTANT:'),
SEP='\n'),
deepseek_coder=dict(
SYSTEM=('You are an AI programming assistant, utilizing '
'the DeepSeek Coder model, developed by DeepSeek'
'Company, and you only answer questions related '
'to computer science. For politically sensitive '
'questions, security and privacy issues, and '
'other non-computer science questions, you will '
'refuse to answer. {system}\n'),
INSTRUCTION=('### Instruction:\n{input}\n### Response:\n'),
SEP='\n'),
# TODO: deprecation, v0.2.0
deepseekcoder=dict(
SYSTEM=('You are an AI programming assistant, utilizing '
'the DeepSeek Coder model, developed by DeepSeek'
'Company, and you only answer questions related '
'to computer science. For politically sensitive '
'questions, security and privacy issues, and '
'other non-computer science questions, you will '
'refuse to answer. {system}\n'),
INSTRUCTION=('### Instruction:\n{input}\n### Response:\n'),
SEP='\n'),
deepseek_moe=dict(
SYSTEM=('[INST] {system} [/INST]\n'),
INSTRUCTION=('[INST] {input} [/INST]'),
SEP='\n'),
deepseek_v2=dict(
SYSTEM='{system}\n\n',
INSTRUCTION='User: {input}\n\nAssistant: ',
SUFFIX='<｜end▁of▁sentence｜>',
SUFFIX_AS_EOS=True,
STOP_WORDS=['<｜end▁of▁sentence｜>']),
mistral=dict(
SYSTEM=('[INST] {system} [/INST]\n'),
INSTRUCTION=('[INST] {input} [/INST]'),
SEP='\n'),
mixtral=dict(
SYSTEM=('[INST] {system} [/INST]\n'),
INSTRUCTION=('[INST] {input} [/INST]'),
SEP='\n'),
gemma=dict(
# `system` field is extended by xtuner
SYSTEM=('<start_of_turn>system\n{system}<end_of_turn>\n'),
INSTRUCTION=('<start_of_turn>user\n{input}<end_of_turn>\n'
'<start_of_turn>model\n'),
SUFFIX='<end_of_turn>',
SUFFIX_AS_EOS=False,
SEP='\n',
STOP_WORDS=['<end_of_turn>']),
cohere_chat=dict(
SYSTEM=('<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>{system}'
'<|END_OF_TURN_TOKEN|>'),
INSTRUCTION=(
'<|START_OF_TURN_TOKEN|><|USER_TOKEN|>{input}<|END_OF_TURN_TOKEN|>'
'<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>'),
SUFFIX='<|END_OF_TURN_TOKEN|>',
SUFFIX_AS_EOS=True,
STOP_WORDS=['<|END_OF_TURN_TOKEN|>']),
llama3_chat=dict(
SYSTEM=('<|start_header_id|>system<|end_header_id|>\n\n'
'{system}<|eot_id|>'),
INSTRUCTION=(
'<|start_header_id|>user<|end_header_id|>\n\n{input}<|eot_id|>'
'<|start_header_id|>assistant<|end_header_id|>\n\n'),
SUFFIX='<|eot_id|>',
SUFFIX_AS_EOS=True,
STOP_WORDS=['<|eot_id|>']),
phi3_chat=dict(
SYSTEM='<|system|>\n{system}<|end|>\n',
INSTRUCTION='<|user|>\n{input}<|end|>\n<|assistant|>\n',
SUFFIX='<|end|>',
SUFFIX_AS_EOS=True,
SEP='\n',
STOP_WORDS=['<|end|>']),
)
SYSTEM_TEMPLATE = ConfigDict(
moss_sft=('You are an AI assistant whose name is {bot_name}.\n'
'Capabilities and tools that {bot_name} can possess.\n'
'- Inner thoughts: enabled.\n'
'- Web search: enabled. API: Search(query)\n'
'- Calculator: enabled. API: Calculate(expression)\n'
'- Equation solver: enabled. API: Solve(equation)\n'
'- Text-to-image: disabled.\n'
'- Image edition: disabled.\n'
'- Text-to-speech: disabled.\n'),
alpaca=('Below is an instruction that describes a task. '
'Write a response that appropriately completes the request.\n'),
arxiv_gentile=('If you are an expert in writing papers, please generate '
"a good paper title for this paper based on other authors' "
'descriptions of their abstracts.\n'),
colorist=('You are a professional color designer. Please provide the '
'corresponding colors based on the description of Human.\n'),
coder=('You are a professional programer. Please provide the '
'corresponding code based on the description of Human.\n'),
lawyer='你现在是一名专业的中国律师，请根据用户的问题给出准确、有理有据的回复。\n',
medical='如果你是一名医生，请根据患者的描述回答医学问题。\n',
sql=('If you are an expert in SQL, please generate a good SQL Query '
'for Question based on the CREATE TABLE statement.\n'),
)
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