mirror of
https://github.com/hiyouga/LLaMA-Factory.git
synced 2025-12-15 03:10:35 +08:00
808 lines
30 KiB
Python
808 lines
30 KiB
Python
from dataclasses import dataclass
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from typing import TYPE_CHECKING, Dict, List, Optional, Sequence, Tuple, Union
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from ..extras.logging import get_logger
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from .formatter import EmptyFormatter, FunctionFormatter, StringFormatter, ToolFormatter
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from .utils import Role, infer_max_len
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if TYPE_CHECKING:
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from transformers import PreTrainedTokenizer
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from .formatter import SLOTS, Formatter
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logger = get_logger(__name__)
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@dataclass
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class Template:
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format_user: "Formatter"
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format_assistant: "Formatter"
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format_system: "Formatter"
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format_function: "Formatter"
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format_observation: "Formatter"
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format_tools: "Formatter"
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format_separator: "Formatter"
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default_system: str
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stop_words: List[str]
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efficient_eos: bool
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replace_eos: bool
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force_system: bool
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def encode_oneturn(
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self,
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tokenizer: "PreTrainedTokenizer",
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messages: List[Dict[str, str]],
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system: Optional[str] = None,
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tools: Optional[str] = None,
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cutoff_len: int = 1_000_000,
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reserved_label_len: int = 1,
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) -> Tuple[List[int], List[int]]:
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r"""
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Returns a single pair of token ids representing prompt and response respectively.
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"""
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encoded_pairs = self._encode(tokenizer, messages, system, tools, cutoff_len, reserved_label_len)
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prompt_ids = []
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for query_ids, resp_ids in encoded_pairs[:-1]:
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prompt_ids += query_ids + resp_ids
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prompt_ids = prompt_ids + encoded_pairs[-1][0]
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answer_ids = encoded_pairs[-1][1]
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return prompt_ids, answer_ids
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def encode_multiturn(
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self,
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tokenizer: "PreTrainedTokenizer",
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messages: List[Dict[str, str]],
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system: Optional[str] = None,
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tools: Optional[str] = None,
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cutoff_len: int = 1_000_000,
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reserved_label_len: int = 1,
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) -> Sequence[Tuple[List[int], List[int]]]:
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r"""
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Returns multiple pairs of token ids representing prompts and responses respectively.
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"""
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return self._encode(tokenizer, messages, system, tools, cutoff_len, reserved_label_len)
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def _encode(
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self,
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tokenizer: "PreTrainedTokenizer",
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messages: List[Dict[str, str]],
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system: str,
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tools: str,
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cutoff_len: int,
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reserved_label_len: int,
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) -> Sequence[Tuple[List[int], List[int]]]:
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r"""
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Encodes formatted inputs to pairs of token ids.
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Turn 0: system + query resp
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Turn t: sep + query resp
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"""
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system = system or self.default_system
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encoded_messages = []
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for i, message in enumerate(messages):
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elements = []
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if i == 0 and (system or tools or self.force_system):
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tool_text = self.format_tools.apply(content=tools)[0] if tools else ""
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elements += self.format_system.apply(content=(system + tool_text))
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elif i > 0 and i % 2 == 0:
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elements += self.format_separator.apply()
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if message["role"] == Role.USER.value:
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elements += self.format_user.apply(content=message["content"], idx=str(i // 2))
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elif message["role"] == Role.ASSISTANT.value:
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elements += self.format_assistant.apply(content=message["content"])
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elif message["role"] == Role.OBSERVATION.value:
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elements += self.format_observation.apply(content=message["content"])
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elif message["role"] == Role.FUNCTION.value:
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elements += self.format_function.apply(content=message["content"])
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else:
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raise NotImplementedError("Unexpected role: {}".format(message["role"]))
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encoded_messages.append(self._convert_elements_to_ids(tokenizer, elements))
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return self._make_pairs(encoded_messages, cutoff_len, reserved_label_len)
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def _convert_elements_to_ids(
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self, tokenizer: "PreTrainedTokenizer", elements: List[Union[str, Dict[str, str]]]
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) -> List[int]:
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r"""
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Converts elements to token ids.
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"""
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token_ids = []
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for elem in elements:
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if isinstance(elem, str):
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if len(elem) != 0:
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token_ids += tokenizer.encode(elem, add_special_tokens=False)
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elif isinstance(elem, dict):
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token_ids += [tokenizer.convert_tokens_to_ids(elem.get("token"))]
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elif isinstance(elem, set):
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if "bos_token" in elem and tokenizer.bos_token_id is not None:
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token_ids += [tokenizer.bos_token_id]
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elif "eos_token" in elem and tokenizer.eos_token_id is not None:
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token_ids += [tokenizer.eos_token_id]
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else:
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raise ValueError("Input must be string, set[str] or dict[str, str], got {}".format(type(elem)))
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return token_ids
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def _make_pairs(
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self,
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encoded_messages: Sequence[List[int]],
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cutoff_len: int,
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reserved_label_len: int,
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) -> Sequence[Tuple[List[int], List[int]]]:
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encoded_pairs = []
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total_length = 0
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for i in range(0, len(encoded_messages), 2):
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if total_length >= cutoff_len:
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break
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max_source_len, max_target_len = infer_max_len(
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source_len=len(encoded_messages[i]),
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target_len=len(encoded_messages[i + 1]),
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max_len=(cutoff_len - total_length),
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reserved_label_len=reserved_label_len,
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)
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source_ids = encoded_messages[i][:max_source_len]
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target_ids = encoded_messages[i + 1][:max_target_len]
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total_length += len(source_ids) + len(target_ids)
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encoded_pairs.append((source_ids, target_ids))
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return encoded_pairs
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@dataclass
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class Llama2Template(Template):
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def _encode(
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self,
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tokenizer: "PreTrainedTokenizer",
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messages: List[Dict[str, str]],
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system: str,
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tools: str,
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cutoff_len: int,
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reserved_label_len: int,
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) -> Sequence[Tuple[List[int], List[int]]]:
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r"""
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Encodes formatted inputs to pairs of token ids.
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Turn 0: system + query resp
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Turn t: sep + query resp
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"""
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system = system or self.default_system
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encoded_messages = []
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for i, message in enumerate(messages):
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elements = []
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system_text = ""
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if i == 0 and (system or tools or self.force_system):
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tool_text = self.format_tools.apply(content=tools)[0] if tools else ""
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system_text = self.format_system.apply(content=(system + tool_text))[0]
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elif i > 0 and i % 2 == 0:
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elements += self.format_separator.apply()
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if message["role"] == Role.USER.value:
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elements += self.format_user.apply(content=system_text + message["content"])
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elif message["role"] == Role.ASSISTANT.value:
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elements += self.format_assistant.apply(content=message["content"])
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elif message["role"] == Role.OBSERVATION.value:
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elements += self.format_observation.apply(content=message["content"])
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elif message["role"] == Role.FUNCTION.value:
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elements += self.format_function.apply(content=message["content"])
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else:
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raise NotImplementedError("Unexpected role: {}".format(message["role"]))
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encoded_messages.append(self._convert_elements_to_ids(tokenizer, elements))
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return self._make_pairs(encoded_messages, cutoff_len, reserved_label_len)
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templates: Dict[str, Template] = {}
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def _register_template(
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name: str,
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format_user: Optional["Formatter"] = None,
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format_assistant: Optional["Formatter"] = None,
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format_system: Optional["Formatter"] = None,
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format_function: Optional["Formatter"] = None,
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format_observation: Optional["Formatter"] = None,
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format_tools: Optional["Formatter"] = None,
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format_separator: Optional["Formatter"] = None,
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default_system: str = "",
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stop_words: List[str] = [],
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efficient_eos: bool = False,
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replace_eos: bool = False,
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force_system: bool = False,
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) -> None:
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r"""
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Registers a chat template.
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To add the following chat template:
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```
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[HUMAN]:
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user prompt here
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[AI]:
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model response here
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[HUMAN]:
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user prompt here
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[AI]:
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model response here
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```
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The corresponding code should be:
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```
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_register_template(
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name="custom",
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format_user=StringFormatter(slots=["[HUMAN]:\n{{content}}\n[AI]:\n"]),
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format_separator=EmptyFormatter(slots=["\n\n"]),
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efficient_eos=True,
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)
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```
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"""
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eos_slots = [] if efficient_eos else [{"eos_token"}]
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template_class = Llama2Template if name.startswith("llama2") else Template
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default_user_formatter = StringFormatter(slots=["{{content}}"])
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default_assistant_formatter = StringFormatter(slots=["{{content}}"] + eos_slots)
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default_function_formatter = FunctionFormatter(slots=["Action: {{name}}\nAction Input: {{arguments}}"] + eos_slots)
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default_tool_formatter = ToolFormatter(tool_format="default")
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default_separator_formatter = EmptyFormatter()
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templates[name] = template_class(
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format_user=format_user or default_user_formatter,
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format_assistant=format_assistant or default_assistant_formatter,
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format_system=format_system or default_user_formatter,
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format_function=format_function or default_function_formatter,
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format_observation=format_observation or format_user or default_user_formatter,
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format_tools=format_tools or default_tool_formatter,
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format_separator=format_separator or default_separator_formatter,
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default_system=default_system,
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stop_words=stop_words,
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efficient_eos=efficient_eos,
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replace_eos=replace_eos,
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force_system=force_system,
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)
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def _add_or_replace_eos_token(tokenizer: "PreTrainedTokenizer", eos_token: str) -> None:
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is_added = tokenizer.eos_token_id is None
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num_added_tokens = tokenizer.add_special_tokens({"eos_token": eos_token})
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if is_added:
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logger.info("Add eos token: {}".format(tokenizer.eos_token))
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else:
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logger.info("Replace eos token: {}".format(tokenizer.eos_token))
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if num_added_tokens > 0:
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logger.warning("New tokens have been added, make sure `resize_vocab` is True.")
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def _jinja_escape(content: str) -> str:
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return content.replace("\n", r"\n").replace("'", r"\'")
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def _convert_slots_to_jinja(slots: "SLOTS", tokenizer: "PreTrainedTokenizer", placeholder: str = "content") -> str:
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slot_items = []
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for slot in slots:
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if isinstance(slot, str):
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slot_pieces = slot.split("{{content}}")
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if slot_pieces[0]:
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slot_items.append("'" + _jinja_escape(slot_pieces[0]) + "'")
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if len(slot_pieces) > 1:
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slot_items.append(placeholder)
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if slot_pieces[1]:
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slot_items.append("'" + _jinja_escape(slot_pieces[1]) + "'")
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elif isinstance(slot, set):
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if "bos_token" in slot:
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slot_items.append("'" + tokenizer.bos_token + "'")
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elif "eos_token" in slot: # do not use {{ eos_token }} since it may be replaced
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slot_items.append("'" + tokenizer.eos_token + "'")
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elif isinstance(slot, dict):
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raise ValueError("Dict is not supported.")
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return " + ".join(slot_items)
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def _get_jinja_template(template: "Template", tokenizer: "PreTrainedTokenizer") -> str:
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jinja_template = ""
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if template.default_system:
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jinja_template += "{% set system_message = '" + _jinja_escape(template.default_system) + "' %}"
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jinja_template += (
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"{% if messages[0]['role'] == 'system' %}" "{% set system_message = messages[0]['content'] %}" "{% endif %}"
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)
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system_message = _convert_slots_to_jinja(template.format_system.apply(), tokenizer, placeholder="system_message")
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if isinstance(template, Llama2Template):
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pass
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elif template.force_system:
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jinja_template += "{{ " + system_message + " }}"
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else:
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jinja_template += "{% if system_message is defined %}{{ " + system_message + " }}{% endif %}"
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jinja_template += "{% for message in messages %}"
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jinja_template += "{% set content = message['content'] %}"
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if isinstance(template, Llama2Template):
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jinja_template += "{% if loop.index0 == 0 and system_message is defined %}"
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jinja_template += "{% set content = " + system_message + " + message['content'] %}"
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jinja_template += "{% endif %}"
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jinja_template += "{% if message['role'] == 'user' %}"
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user_message = _convert_slots_to_jinja(template.format_user.apply(), tokenizer)
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jinja_template += "{{ " + user_message + " }}"
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jinja_template += "{% elif message['role'] == 'assistant' %}"
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assistant_message = _convert_slots_to_jinja(
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template.format_assistant.apply() + template.format_separator.apply(), tokenizer
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)
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jinja_template += "{{ " + assistant_message + " }}"
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jinja_template += "{% endif %}"
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jinja_template += "{% endfor %}"
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return jinja_template
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def get_template_and_fix_tokenizer(
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tokenizer: "PreTrainedTokenizer",
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name: Optional[str] = None,
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) -> Template:
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if name is None:
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template = templates["vanilla"] # placeholder
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else:
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template = templates.get(name, None)
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if template is None:
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raise ValueError("Template {} does not exist.".format(name))
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stop_words = template.stop_words
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if template.replace_eos:
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if not stop_words:
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raise ValueError("Stop words are required to replace the EOS token.")
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_add_or_replace_eos_token(tokenizer, eos_token=stop_words[0])
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stop_words = stop_words[1:]
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if tokenizer.eos_token_id is None:
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_add_or_replace_eos_token(tokenizer, eos_token="<|endoftext|>")
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if tokenizer.pad_token_id is None:
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tokenizer.pad_token = tokenizer.eos_token
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logger.info("Add pad token: {}".format(tokenizer.pad_token))
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if stop_words:
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num_added_tokens = tokenizer.add_special_tokens(
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dict(additional_special_tokens=stop_words), replace_additional_special_tokens=False
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)
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logger.info("Add {} to stop words.".format(",".join(stop_words)))
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if num_added_tokens > 0:
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logger.warning("New tokens have been added, make sure `resize_vocab` is True.")
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try:
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tokenizer.chat_template = _get_jinja_template(template, tokenizer)
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except ValueError:
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logger.info("Cannot add this chat template to tokenizer.")
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return template
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_register_template(
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name="alpaca",
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format_user=StringFormatter(slots=["### Instruction:\n{{content}}\n\n### Response:\n"]),
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format_separator=EmptyFormatter(slots=["\n\n"]),
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default_system=(
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"Below is an instruction that describes a task. " "Write a response that appropriately completes the request."
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),
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)
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_register_template(
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name="aquila",
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format_user=StringFormatter(slots=["Human: {{content}}###Assistant:"]),
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format_separator=EmptyFormatter(slots=["###"]),
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default_system=(
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"A chat between a curious human and an artificial intelligence assistant. "
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"The assistant gives helpful, detailed, and polite answers to the human's questions."
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),
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stop_words=["</s>"],
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efficient_eos=True,
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)
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_register_template(
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name="atom",
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format_user=StringFormatter(
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slots=[{"bos_token"}, "Human: {{content}}\n", {"eos_token"}, {"bos_token"}, "Assistant:"]
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),
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format_assistant=StringFormatter(slots=["{{content}}\n", {"eos_token"}]),
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)
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_register_template(
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name="baichuan",
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format_user=StringFormatter(slots=[{"token": "<reserved_102>"}, "{{content}}", {"token": "<reserved_103>"}]),
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efficient_eos=True,
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)
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_register_template(
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name="baichuan2",
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format_user=StringFormatter(slots=["<reserved_106>{{content}}<reserved_107>"]),
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efficient_eos=True,
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)
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_register_template(
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name="belle",
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format_user=StringFormatter(slots=["Human: {{content}}\n\nBelle: "]),
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format_system=StringFormatter(slots=[{"bos_token"}, "{{content}}"]),
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format_separator=EmptyFormatter(slots=["\n\n"]),
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force_system=True,
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)
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_register_template(
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name="bluelm",
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format_user=StringFormatter(slots=[{"token": "[|Human|]:"}, "{{content}}", {"token": "[|AI|]:"}]),
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)
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_register_template(
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name="breeze",
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format_user=StringFormatter(slots=["[INST] {{content}} [/INST] "]),
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format_system=StringFormatter(slots=[{"bos_token"}, "{{content}}"]),
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default_system=(
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"You are a helpful AI assistant built by MediaTek Research. "
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"The user you are helping speaks Traditional Chinese and comes from Taiwan."
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),
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efficient_eos=True,
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)
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_register_template(
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name="chatglm2",
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format_user=StringFormatter(slots=["[Round {{idx}}]\n\n问：{{content}}\n\n答："]),
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format_system=StringFormatter(slots=[{"token": "[gMASK]"}, {"token": "sop"}, "{{content}}"]),
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format_separator=EmptyFormatter(slots=["\n\n"]),
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efficient_eos=True,
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force_system=True,
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)
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_register_template(
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name="chatglm3",
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format_user=StringFormatter(slots=[{"token": "<|user|>"}, "\n", "{{content}}", {"token": "<|assistant|>"}]),
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format_assistant=StringFormatter(slots=["\n", "{{content}}"]),
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format_system=StringFormatter(slots=[{"token": "[gMASK]"}, {"token": "sop"}, "{{content}}"]),
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format_function=FunctionFormatter(slots=["{{name}}\n{{arguments}}"]),
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format_observation=StringFormatter(
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slots=[{"token": "<|observation|>"}, "\n", "{{content}}", {"token": "<|assistant|>"}]
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),
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stop_words=["<|user|>", "<|observation|>"],
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efficient_eos=True,
|
||
force_system=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="chatglm3_system",
|
||
format_user=StringFormatter(slots=[{"token": "<|user|>"}, "\n", "{{content}}", {"token": "<|assistant|>"}]),
|
||
format_assistant=StringFormatter(slots=["\n", "{{content}}"]),
|
||
format_system=StringFormatter(
|
||
slots=[{"token": "[gMASK]"}, {"token": "sop"}, {"token": "<|system|>"}, "\n", "{{content}}"]
|
||
),
|
||
format_function=FunctionFormatter(slots=["{{name}}\n{{arguments}}"]),
|
||
format_observation=StringFormatter(
|
||
slots=[{"token": "<|observation|>"}, "\n", "{{content}}", {"token": "<|assistant|>"}]
|
||
),
|
||
default_system=(
|
||
"You are ChatGLM3, a large language model trained by Zhipu.AI. "
|
||
"Follow the user's instructions carefully. Respond using markdown."
|
||
),
|
||
stop_words=["<|user|>", "<|observation|>"],
|
||
efficient_eos=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="chatml",
|
||
format_user=StringFormatter(slots=["<|im_start|>user\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
|
||
format_system=StringFormatter(slots=["<|im_start|>system\n{{content}}<|im_end|>\n"]),
|
||
format_separator=EmptyFormatter(slots=["\n"]),
|
||
stop_words=["<|im_end|>", "<|im_start|>"],
|
||
replace_eos=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="chatml_de",
|
||
format_user=StringFormatter(slots=["<|im_start|>user\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
|
||
format_system=StringFormatter(slots=["<|im_start|>system\n{{content}}<|im_end|>\n"]),
|
||
format_separator=EmptyFormatter(slots=["\n"]),
|
||
default_system="Du bist ein freundlicher und hilfsbereiter KI-Assistent.",
|
||
stop_words=["<|im_end|>", "<|im_start|>"],
|
||
replace_eos=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="codegeex2",
|
||
format_system=StringFormatter(slots=[{"token": "[gMASK]"}, {"token": "sop"}, "{{content}}"]),
|
||
force_system=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="cpm",
|
||
format_user=StringFormatter(slots=["<用户>{{content}}<AI>"]),
|
||
format_system=StringFormatter(slots=[{"bos_token"}, "{{content}}"]),
|
||
force_system=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="deepseek",
|
||
format_user=StringFormatter(slots=["User: {{content}}\n\nAssistant:"]),
|
||
format_system=StringFormatter(slots=[{"bos_token"}, "{{content}}"]),
|
||
force_system=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="deepseekcoder",
|
||
format_user=StringFormatter(slots=["### Instruction:\n{{content}}\n### Response:"]),
|
||
format_assistant=StringFormatter(slots=["\n", "{{content}}"]),
|
||
format_separator=EmptyFormatter(slots=["\n<|EOT|>\n"]),
|
||
default_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\n"
|
||
),
|
||
stop_words=["<|EOT|>"],
|
||
efficient_eos=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="default",
|
||
format_user=StringFormatter(slots=["Human: {{content}}\nAssistant: "]),
|
||
format_system=StringFormatter(slots=["{{content}}\n"]),
|
||
format_separator=EmptyFormatter(slots=["\n"]),
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="falcon",
|
||
format_user=StringFormatter(slots=["User: {{content}}\nFalcon:"]),
|
||
format_separator=EmptyFormatter(slots=["\n"]),
|
||
efficient_eos=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="gemma",
|
||
format_user=StringFormatter(slots=["<start_of_turn>user\n{{content}}<end_of_turn>\n<start_of_turn>model\n"]),
|
||
format_system=StringFormatter(slots=[{"bos_token"}, "{{content}}"]),
|
||
format_separator=EmptyFormatter(slots=["<end_of_turn>\n"]),
|
||
efficient_eos=True,
|
||
force_system=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="intern",
|
||
format_user=StringFormatter(slots=["<|User|>:{{content}}", {"token": "<eoh>"}, "\n<|Bot|>:"]),
|
||
format_separator=EmptyFormatter(slots=[{"token": "<eoa>"}, "\n"]),
|
||
stop_words=["<eoa>"],
|
||
efficient_eos=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="intern2",
|
||
format_user=StringFormatter(slots=["<|im_start|>user\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
|
||
format_system=StringFormatter(slots=[{"bos_token"}, "<|im_start|>system\n{{content}}<|im_end|>\n"]),
|
||
format_separator=EmptyFormatter(slots=["\n"]),
|
||
default_system=(
|
||
"You are an AI assistant whose name is InternLM (书生·浦语).\n"
|
||
"- InternLM (书生·浦语) is a conversational language model that is developed "
|
||
"by Shanghai AI Laboratory (上海人工智能实验室). It is designed to be helpful, honest, and harmless.\n"
|
||
"- InternLM (书生·浦语) can understand and communicate fluently in the language chosen "
|
||
"by the user such as English and 中文."
|
||
),
|
||
stop_words=["<|im_end|>"],
|
||
efficient_eos=True, # internlm2 tokenizer cannot set eos_token_id
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="llama2",
|
||
format_user=StringFormatter(slots=[{"bos_token"}, "[INST] {{content}} [/INST]"]),
|
||
format_system=StringFormatter(slots=["<<SYS>>\n{{content}}\n<</SYS>>\n\n"]),
|
||
default_system=(
|
||
"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\n"
|
||
"If a question does not make any sense, or is not factually coherent, "
|
||
"explain why instead of answering something not correct. "
|
||
"If you don't know the answer to a question, please don't share false information."
|
||
),
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="llama2_zh",
|
||
format_user=StringFormatter(slots=[{"bos_token"}, "[INST] {{content}} [/INST]"]),
|
||
format_system=StringFormatter(slots=["<<SYS>>\n{{content}}\n<</SYS>>\n\n"]),
|
||
default_system="You are a helpful assistant. 你是一个乐于助人的助手。",
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="mistral",
|
||
format_user=StringFormatter(slots=["[INST] {{content}} [/INST]"]),
|
||
format_system=StringFormatter(slots=[{"bos_token"}, "{{content}}"]),
|
||
force_system=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="olmo",
|
||
format_user=StringFormatter(slots=["<|user|>\n{{content}}<|assistant|>"]),
|
||
format_assistant=StringFormatter(slots=["{{content}}", {"eos_token"}]),
|
||
format_system=StringFormatter(slots=[{"eos_token"}, "{{content}}"]),
|
||
force_system=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="openchat",
|
||
format_user=StringFormatter(slots=["GPT4 Correct User: {{content}}", {"eos_token"}, "GPT4 Correct Assistant:"]),
|
||
format_assistant=StringFormatter(slots=["{{content}}", {"eos_token"}]),
|
||
format_system=StringFormatter(slots=[{"bos_token"}, "{{content}}"]),
|
||
force_system=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="orion",
|
||
format_user=StringFormatter(slots=["Human: {{content}}\n\nAssistant: ", {"eos_token"}]),
|
||
format_system=StringFormatter(slots=[{"bos_token"}, "{{content}}"]),
|
||
force_system=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="qwen",
|
||
format_user=StringFormatter(slots=["<|im_start|>user\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
|
||
format_system=StringFormatter(slots=["<|im_start|>system\n{{content}}<|im_end|>\n"]),
|
||
format_separator=EmptyFormatter(slots=["\n"]),
|
||
default_system="You are a helpful assistant.",
|
||
stop_words=["<|im_end|>"],
|
||
replace_eos=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="solar",
|
||
format_user=StringFormatter(slots=["### User:\n{{content}}\n\n### Assistant:\n"]),
|
||
format_system=StringFormatter(slots=["### System:\n{{content}}\n\n"]),
|
||
efficient_eos=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="starchat",
|
||
format_user=StringFormatter(slots=["<|user|>\n{{content}}<|end|>\n<|assistant|>"]),
|
||
format_system=StringFormatter(slots=["<|system|>\n{{content}}<|end|>\n"]),
|
||
format_separator=EmptyFormatter(slots=["\n"]),
|
||
stop_words=["<|end|>"],
|
||
replace_eos=True,
|
||
force_system=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="vanilla",
|
||
format_separator=EmptyFormatter(slots=["\n"]),
|
||
efficient_eos=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="vicuna",
|
||
format_user=StringFormatter(slots=["USER: {{content}} ASSISTANT:"]),
|
||
default_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."
|
||
),
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="xuanyuan",
|
||
format_user=StringFormatter(slots=["Human: {{content}} Assistant:"]),
|
||
default_system=(
|
||
"以下是用户和人工智能助手之间的对话。用户以Human开头，人工智能助手以Assistant开头，"
|
||
"会对人类提出的问题给出有帮助、高质量、详细和礼貌的回答，并且总是拒绝参与与不道德、"
|
||
"不安全、有争议、政治敏感等相关的话题、问题和指示。\n"
|
||
),
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="xverse",
|
||
format_user=StringFormatter(slots=["Human: {{content}}\n\nAssistant: "]),
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="yayi",
|
||
format_user=StringFormatter(slots=[{"token": "<|Human|>"}, ":\n{{content}}\n\n", {"token": "<|YaYi|>"}, ":"]),
|
||
format_system=StringFormatter(slots=[{"token": "<|System|>"}, ":\n{{content}}\n\n"]),
|
||
format_separator=EmptyFormatter(slots=["\n\n"]),
|
||
default_system=(
|
||
"You are a helpful, respectful and honest assistant named YaYi "
|
||
"developed by Beijing Wenge Technology Co.,Ltd. "
|
||
"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\n"
|
||
"If a question does not make any sense, or is not factually coherent, "
|
||
"explain why instead of answering something not correct. "
|
||
"If you don't know the answer to a question, please don't share false information."
|
||
),
|
||
stop_words=["<|End|>"],
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="yi",
|
||
format_user=StringFormatter(slots=["<|im_start|>user\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
|
||
format_separator=EmptyFormatter(slots=["\n"]),
|
||
stop_words=["<|im_end|>"],
|
||
replace_eos=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="yuan",
|
||
format_user=StringFormatter(slots=["{{content}}", {"token": "<sep>"}]),
|
||
format_separator=EmptyFormatter(slots=["\n"]),
|
||
stop_words=["<eod>"],
|
||
replace_eos=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="zephyr",
|
||
format_user=StringFormatter(slots=["<|user|>\n{{content}}", {"eos_token"}, "<|assistant|>"]),
|
||
format_assistant=StringFormatter(slots=["\n{{content}}", {"eos_token"}]),
|
||
format_system=StringFormatter(slots=["<|system|>\n{{content}}", {"eos_token"}]),
|
||
default_system="You are a friendly chatbot who always responds in the style of a pirate",
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="ziya",
|
||
format_user=StringFormatter(slots=["<human>:{{content}}\n<bot>:"]),
|
||
format_separator=EmptyFormatter(slots=["\n"]),
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="c4ai",
|
||
format_user=StringFormatter(slots=["<|START_OF_TURN_TOKEN|><|USER_TOKEN|>{{content}}", "<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>"]),
|
||
format_assistant=StringFormatter(slots=["{{content}}", "<|END_OF_TURN_TOKEN|>"]),
|
||
format_system=StringFormatter(slots=[{"bos_token"},"<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>{{content}}", "<|END_OF_TURN_TOKEN|>"]),
|
||
format_observation=StringFormatter(slots=["<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>{{content}}", "<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>"]),
|
||
default_system=(
|
||
"# Safety Preamble\n",
|
||
"The instructions in this section override those in the task description and style guide sections. Don't answer questions that are harmful or immoral.\n\n",
|
||
"# System Preamble\n",
|
||
"## Basic Rules\n",
|
||
"You are a powerful conversational AI trained by Cohere to help people. You are augmented by a number of tools, and your job is to use and consume the output of these tools to best help the user. You will see a conversation history between yourself and a user, ending with an utterance from the user. You will then see a specific instruction instructing you what kind of response to generate. When you answer the user's requests, you cite your sources in your answers, according to those instructions.\n\n",
|
||
"# User Preamble\n",
|
||
"## Task and Context\n",
|
||
"You help people answer their questions and other requests interactively. You will be asked a very wide array of requests on all kinds of topics. You will be equipped with a wide range of search engines or similar tools to help you, which you use to research your answer. You should focus on serving the user's needs as best you can, which will be wide-ranging.\n\n",
|
||
"## Style Guide\n",
|
||
"Unless the user asks for a different style of answer, you should answer in full sentences, using proper grammar and spelling."
|
||
)
|
||
) |