mirror of
https://github.com/hiyouga/LLaMA-Factory.git
synced 2025-08-02 11:42:49 +08:00
830 lines
29 KiB
Python
830 lines
29 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["empty"] # 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. "
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"Write a response that appropriately completes the request.\n\n"
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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|>"],
|
||
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="cohere",
|
||
format_user=StringFormatter(
|
||
slots=[
|
||
(
|
||
"<|START_OF_TURN_TOKEN|><|USER_TOKEN|>{{content}}<|END_OF_TURN_TOKEN|>"
|
||
"<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>"
|
||
)
|
||
]
|
||
),
|
||
format_system=EmptyFormatter(slots=[{"bos_token"}]),
|
||
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="empty",
|
||
format_user=StringFormatter(slots=["{{content}}"]),
|
||
format_assistant=StringFormatter(slots=["{{content}}"]),
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="falcon",
|
||
format_user=StringFormatter(slots=["User: {{content}}\nFalcon:"]),
|
||
format_separator=EmptyFormatter(slots=["\n"]),
|
||
efficient_eos=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="fewshot",
|
||
format_separator=EmptyFormatter(slots=["\n\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="llama3",
|
||
format_user=StringFormatter(
|
||
slots=[
|
||
(
|
||
"<|start_header_id|>user<|end_header_id|>\n\n{{content}}<|eot_id|>"
|
||
"<|start_header_id|>assistant<|end_header_id|>\n\n"
|
||
)
|
||
]
|
||
),
|
||
format_system=StringFormatter(
|
||
slots=[{"bos_token"}, "<|start_header_id|>system<|end_header_id|>\n\n{{content}}<|eot_id|>"]
|
||
),
|
||
default_system="You are a helpful assistant.",
|
||
stop_words=["<|eot_id|>"],
|
||
replace_eos=True,
|
||
)
|
||
|
||
|
||
_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="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"]),
|
||
)
|