mirror of
https://github.com/hiyouga/LLaMA-Factory.git
synced 2025-08-02 11:42:49 +08:00
1293 lines
48 KiB
Python
1293 lines
48 KiB
Python
# Copyright 2024 the LlamaFactory team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from dataclasses import dataclass
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from typing import TYPE_CHECKING, Dict, List, Optional, Sequence, Tuple, Union
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from transformers.utils.versions import require_version
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from typing_extensions import override
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from ..extras import logging
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from .data_utils import Role
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from .formatter import EmptyFormatter, FunctionFormatter, StringFormatter, ToolFormatter
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from .mm_plugin import get_mm_plugin
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if TYPE_CHECKING:
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from transformers import PreTrainedTokenizer
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from ..hparams import DataArguments
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from .formatter import SLOTS, Formatter
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from .mm_plugin import BasePlugin
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from .tool_utils import FunctionCall
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logger = logging.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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format_prefix: "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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replace_jinja_template: bool
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mm_plugin: "BasePlugin"
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def encode_oneturn(
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self,
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tokenizer: "PreTrainedTokenizer",
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messages: Sequence[Dict[str, str]],
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system: Optional[str] = None,
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tools: Optional[str] = None,
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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_messages = self._encode(tokenizer, messages, system, tools)
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prompt_ids = []
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for encoded_ids in encoded_messages[:-1]:
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prompt_ids += encoded_ids
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answer_ids = encoded_messages[-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: Sequence[Dict[str, str]],
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system: Optional[str] = None,
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tools: Optional[str] = None,
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) -> List[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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encoded_messages = self._encode(tokenizer, messages, system, tools)
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return [(encoded_messages[i], encoded_messages[i + 1]) for i in range(0, len(encoded_messages), 2)]
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def extract_tool(self, content: str) -> Union[str, List["FunctionCall"]]:
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r"""
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Extracts tool message.
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"""
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return self.format_tools.extract(content)
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def _encode(
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self,
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tokenizer: "PreTrainedTokenizer",
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messages: Sequence[Dict[str, str]],
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system: Optional[str],
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tools: Optional[str],
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) -> List[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: prefix + 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:
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elements += self.format_prefix.apply()
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if system or tools:
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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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if 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 encoded_messages
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def _convert_elements_to_ids(self, tokenizer: "PreTrainedTokenizer", elements: "SLOTS") -> 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(f"Input must be string, set[str] or dict[str, str], got {type(elem)}")
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return token_ids
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@dataclass
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class Llama2Template(Template):
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@override
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def _encode(
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self,
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tokenizer: "PreTrainedTokenizer",
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messages: Sequence[Dict[str, str]],
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system: str,
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tools: str,
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) -> List[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: prefix + 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:
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elements += self.format_prefix.apply()
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if system or tools:
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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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if 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 encoded_messages
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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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format_prefix: Optional["Formatter"] = None,
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default_system: str = "",
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stop_words: Sequence[str] = [],
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efficient_eos: bool = False,
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replace_eos: bool = False,
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replace_jinja_template: bool = False,
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mm_plugin: "BasePlugin" = get_mm_plugin(name="base"),
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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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template_class = Llama2Template if any(k in name for k in ("llama2", "mistral")) else Template
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default_slots = ["{{content}}"] if efficient_eos else ["{{content}}", {"eos_token"}]
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default_user_formatter = StringFormatter(slots=["{{content}}"])
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default_assistant_formatter = StringFormatter(slots=default_slots)
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default_function_formatter = FunctionFormatter(slots=default_slots, tool_format="default")
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default_tool_formatter = ToolFormatter(tool_format="default")
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default_separator_formatter = EmptyFormatter()
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default_prefix_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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format_prefix=format_prefix or default_prefix_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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replace_jinja_template=replace_jinja_template,
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mm_plugin=mm_plugin,
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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_rank0(f"Add eos token: {tokenizer.eos_token}")
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else:
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logger.info_rank0(f"Replace eos token: {tokenizer.eos_token}")
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if num_added_tokens > 0:
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logger.warning_rank0("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("'", 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): # do not use {{ eos_token }} since it may be replaced
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if "bos_token" in slot and tokenizer.bos_token_id is not None:
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slot_items.append("'" + tokenizer.bos_token + "'")
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elif "eos_token" in slot and tokenizer.eos_token_id is not None:
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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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r"""
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Returns the jinja template.
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"""
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jinja_template = ""
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prefix = _convert_slots_to_jinja(template.format_prefix.apply(), tokenizer)
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if prefix:
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jinja_template += "{{ " + prefix + " }}"
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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 loop_messages = messages[1:] %}"
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"{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% 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 not isinstance(template, Llama2Template):
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jinja_template += "{% if system_message is defined %}{{ " + system_message + " }}{% endif %}"
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jinja_template += "{% for message in loop_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(tokenizer: "PreTrainedTokenizer", data_args: "DataArguments") -> "Template":
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r"""
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Gets chat template and fixes the tokenizer.
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"""
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if data_args.template is None:
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template = TEMPLATES["empty"] # placeholder
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else:
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template = TEMPLATES.get(data_args.template, None)
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if template is None:
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raise ValueError(f"Template {data_args.template} does not exist.")
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if template.mm_plugin.__class__.__name__ != "BasePlugin":
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require_version("transformers>=4.45.0", "To fix: pip install transformers>=4.45.0")
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if data_args.train_on_prompt and template.efficient_eos:
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raise ValueError("Current template does not support `train_on_prompt`.")
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if data_args.tool_format is not None:
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logger.info_rank0(f"Using tool format: {data_args.tool_format}.")
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default_slots = ["{{content}}"] if template.efficient_eos else ["{{content}}", {"eos_token"}]
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template.format_function = FunctionFormatter(slots=default_slots, tool_format=data_args.tool_format)
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template.format_tools = ToolFormatter(tool_format=data_args.tool_format)
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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_rank0(f"Add pad token: {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_rank0("Add {} to stop words.".format(",".join(stop_words)))
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if num_added_tokens > 0:
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logger.warning_rank0("New tokens have been added, make sure `resize_vocab` is True.")
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if tokenizer.chat_template is None or template.replace_jinja_template:
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try:
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tokenizer.chat_template = _get_jinja_template(template, tokenizer)
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except ValueError as e:
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logger.info_rank0(f"Cannot add this chat template to tokenizer: {e}.")
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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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replace_jinja_template=True,
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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_separator=EmptyFormatter(slots=["\n\n"]),
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||
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
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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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_register_template(
|
||
name="breeze",
|
||
format_user=StringFormatter(slots=["[INST] {{content}} [/INST] "]),
|
||
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
|
||
efficient_eos=True,
|
||
)
|
||
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_register_template(
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||
name="chatglm2",
|
||
format_user=StringFormatter(slots=["[Round {{idx}}]\n\n问：{{content}}\n\n答："]),
|
||
format_separator=EmptyFormatter(slots=["\n\n"]),
|
||
format_prefix=EmptyFormatter(slots=[{"token": "[gMASK]"}, {"token": "sop"}]),
|
||
efficient_eos=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="chatglm3",
|
||
format_user=StringFormatter(slots=[{"token": "<|user|>"}, "\n", "{{content}}", {"token": "<|assistant|>"}]),
|
||
format_assistant=StringFormatter(slots=["\n", "{{content}}"]),
|
||
format_system=StringFormatter(slots=[{"token": "<|system|>"}, "\n", "{{content}}"]),
|
||
format_function=FunctionFormatter(slots=["{{content}}"], tool_format="glm4"),
|
||
format_observation=StringFormatter(
|
||
slots=[{"token": "<|observation|>"}, "\n", "{{content}}", {"token": "<|assistant|>"}]
|
||
),
|
||
format_tools=ToolFormatter(tool_format="glm4"),
|
||
format_prefix=EmptyFormatter(slots=[{"token": "[gMASK]"}, {"token": "sop"}]),
|
||
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_observation=StringFormatter(slots=["<|im_start|>tool\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
|
||
format_separator=EmptyFormatter(slots=["\n"]),
|
||
stop_words=["<|im_end|>", "<|im_start|>"],
|
||
replace_eos=True,
|
||
replace_jinja_template=True,
|
||
)
|
||
|
||
|
||
# copied from chatml template
|
||
_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_observation=StringFormatter(slots=["<|im_start|>tool\n{{content}}<|im_end|>\n<|im_start|>assistant\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,
|
||
replace_jinja_template=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="codegeex2",
|
||
format_prefix=EmptyFormatter(slots=[{"token": "[gMASK]"}, {"token": "sop"}]),
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="codegeex4",
|
||
format_user=StringFormatter(slots=["<|user|>\n{{content}}<|assistant|>\n"]),
|
||
format_system=StringFormatter(slots=["<|system|>\n{{content}}"]),
|
||
format_function=FunctionFormatter(slots=["{{content}}"], tool_format="glm4"),
|
||
format_observation=StringFormatter(slots=["<|observation|>\n{{content}}<|assistant|>\n"]),
|
||
format_tools=ToolFormatter(tool_format="glm4"),
|
||
format_prefix=EmptyFormatter(slots=["[gMASK]<sop>"]),
|
||
default_system=(
|
||
"你是一位智能编程助手，你叫CodeGeeX。你会为用户回答关于编程、代码、计算机方面的任何问题，"
|
||
"并提供格式规范、可以执行、准确安全的代码，并在必要时提供详细的解释。"
|
||
),
|
||
stop_words=["<|user|>", "<|observation|>"],
|
||
efficient_eos=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=StringFormatter(slots=["<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>{{content}}<|END_OF_TURN_TOKEN|>"]),
|
||
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="cpm",
|
||
format_user=StringFormatter(slots=["<用户>{{content}}<AI>"]),
|
||
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="cpm3",
|
||
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_prefix=EmptyFormatter(slots=[{"bos_token"}]),
|
||
stop_words=["<|im_end|>"],
|
||
)
|
||
|
||
|
||
# copied from chatml template
|
||
_register_template(
|
||
name="dbrx",
|
||
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_observation=StringFormatter(slots=["<|im_start|>tool\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
|
||
format_separator=EmptyFormatter(slots=["\n"]),
|
||
default_system=(
|
||
"You are DBRX, created by Databricks. You were last updated in December 2023. "
|
||
"You answer questions based on information available up to that point.\n"
|
||
"YOU PROVIDE SHORT RESPONSES TO SHORT QUESTIONS OR STATEMENTS, but provide thorough "
|
||
"responses to more complex and open-ended questions.\nYou assist with various tasks, "
|
||
"from writing to coding (using markdown for code blocks — remember to use ``` with "
|
||
"code, JSON, and tables).\n(You do not have real-time data access or code execution "
|
||
"capabilities. You avoid stereotyping and provide balanced perspectives on "
|
||
"controversial topics. You do not provide song lyrics, poems, or news articles and "
|
||
"do not divulge details of your training data.)\nThis is your system prompt, "
|
||
"guiding your responses. Do not reference it, just respond to the user. If you find "
|
||
"yourself talking about this message, stop. You should be responding appropriately "
|
||
"and usually that means not mentioning this.\nYOU DO NOT MENTION ANY OF THIS INFORMATION "
|
||
"ABOUT YOURSELF UNLESS THE INFORMATION IS DIRECTLY PERTINENT TO THE USER'S QUERY."
|
||
),
|
||
stop_words=["<|im_end|>"],
|
||
replace_eos=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="deepseek",
|
||
format_user=StringFormatter(slots=["User: {{content}}\n\nAssistant:"]),
|
||
format_system=StringFormatter(slots=["{{content}}\n\n"]),
|
||
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="deepseek3",
|
||
format_user=StringFormatter(slots=["<｜User｜>{{content}}<｜Assistant｜>"]),
|
||
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="deepseekcoder",
|
||
format_user=StringFormatter(slots=["### Instruction:\n{{content}}\n### Response:"]),
|
||
format_assistant=StringFormatter(slots=["\n{{content}}\n<|EOT|>"]),
|
||
format_separator=EmptyFormatter(slots=["\n"]),
|
||
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
|
||
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"
|
||
),
|
||
)
|
||
|
||
|
||
_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",
|
||
efficient_eos=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="exaone",
|
||
format_user=StringFormatter(slots=["[|user|]{{content}}\n[|assistant|]"]),
|
||
format_system=StringFormatter(slots=["[|system|]{{content}}[|endofturn|]\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="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_observation=StringFormatter(
|
||
slots=["<start_of_turn>tool\n{{content}}<end_of_turn>\n<start_of_turn>model\n"]
|
||
),
|
||
format_separator=EmptyFormatter(slots=["<end_of_turn>\n"]),
|
||
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
|
||
efficient_eos=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="glm4",
|
||
format_user=StringFormatter(slots=["<|user|>\n{{content}}<|assistant|>"]),
|
||
format_assistant=StringFormatter(slots=["\n{{content}}"]),
|
||
format_system=StringFormatter(slots=["<|system|>\n{{content}}"]),
|
||
format_function=FunctionFormatter(slots=["{{content}}"], tool_format="glm4"),
|
||
format_observation=StringFormatter(slots=["<|observation|>\n{{content}}<|assistant|>"]),
|
||
format_tools=ToolFormatter(tool_format="glm4"),
|
||
format_prefix=EmptyFormatter(slots=["[gMASK]<sop>"]),
|
||
stop_words=["<|user|>", "<|observation|>"],
|
||
efficient_eos=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="granite3",
|
||
format_user=StringFormatter(
|
||
slots=[
|
||
"<|start_of_role|>user<|end_of_role|>{{content}}<|end_of_text|>\n<|start_of_role|>assistant<|end_of_role|>"
|
||
]
|
||
),
|
||
format_system=StringFormatter(slots=["<|start_of_role|>system<|end_of_role|>{{content}}<|end_of_text|>\n"]),
|
||
format_separator=EmptyFormatter(slots=["\n"]),
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="index",
|
||
format_user=StringFormatter(slots=["reserved_0{{content}}reserved_1"]),
|
||
format_system=StringFormatter(slots=["<unk>{{content}}"]),
|
||
efficient_eos=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="intern",
|
||
format_user=StringFormatter(slots=["<|User|>:{{content}}\n<|Bot|>:"]),
|
||
format_system=StringFormatter(slots=["<|System|>:{{content}}\n"]),
|
||
format_separator=EmptyFormatter(slots=["<eoa>\n"]),
|
||
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
|
||
stop_words=["<eoa>"],
|
||
efficient_eos=True, # internlm tokenizer cannot set eos_token_id
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="intern2",
|
||
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=["<|im_end|>\n"]),
|
||
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
|
||
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"]),
|
||
)
|
||
|
||
|
||
# copied from llama2 template
|
||
_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=["<|start_header_id|>system<|end_header_id|>\n\n{{content}}<|eot_id|>"]),
|
||
format_function=FunctionFormatter(slots=["{{content}}", "<|eot_id|>"], tool_format="llama3"),
|
||
format_observation=StringFormatter(
|
||
slots=[
|
||
(
|
||
"<|start_header_id|>ipython<|end_header_id|>\n\n{{content}}<|eot_id|>"
|
||
"<|start_header_id|>assistant<|end_header_id|>\n\n"
|
||
)
|
||
]
|
||
),
|
||
format_tools=ToolFormatter(tool_format="llama3"),
|
||
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
|
||
stop_words=["<|eot_id|>", "<|eom_id|>"],
|
||
)
|
||
|
||
|
||
# copied from llama3 template
|
||
_register_template(
|
||
name="mllama",
|
||
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=["<|start_header_id|>system<|end_header_id|>\n\n{{content}}<|eot_id|>"]),
|
||
format_function=FunctionFormatter(slots=["{{content}}", "<|eot_id|>"], tool_format="llama3"),
|
||
format_observation=StringFormatter(
|
||
slots=[
|
||
(
|
||
"<|start_header_id|>ipython<|end_header_id|>\n\n{{content}}<|eot_id|>"
|
||
"<|start_header_id|>assistant<|end_header_id|>\n\n"
|
||
)
|
||
]
|
||
),
|
||
format_tools=ToolFormatter(tool_format="llama3"),
|
||
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
|
||
stop_words=["<|eot_id|>", "<|eom_id|>"],
|
||
mm_plugin=get_mm_plugin(name="mllama", image_token="<|image|>"),
|
||
)
|
||
|
||
|
||
# copied from vicuna template
|
||
_register_template(
|
||
name="llava",
|
||
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."
|
||
),
|
||
mm_plugin=get_mm_plugin(name="llava", image_token="<image>"),
|
||
)
|
||
|
||
|
||
# copied from vicuna template
|
||
_register_template(
|
||
name="llava_next",
|
||
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."
|
||
),
|
||
mm_plugin=get_mm_plugin(name="llava_next", image_token="<image>"),
|
||
)
|
||
|
||
|
||
# copied from llama3 template
|
||
_register_template(
|
||
name="llava_next_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=["<|start_header_id|>system<|end_header_id|>\n\n{{content}}<|eot_id|>"]),
|
||
format_function=FunctionFormatter(slots=["{{content}}", "<|eot_id|>"], tool_format="llama3"),
|
||
format_observation=StringFormatter(
|
||
slots=[
|
||
(
|
||
"<|start_header_id|>ipython<|end_header_id|>\n\n{{content}}<|eot_id|>"
|
||
"<|start_header_id|>assistant<|end_header_id|>\n\n"
|
||
)
|
||
]
|
||
),
|
||
format_tools=ToolFormatter(tool_format="llama3"),
|
||
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
|
||
stop_words=["<|eot_id|>", "<|eom_id|>"],
|
||
mm_plugin=get_mm_plugin(name="llava_next", image_token="<image>"),
|
||
)
|
||
|
||
|
||
# copied from mistral template
|
||
_register_template(
|
||
name="llava_next_mistral",
|
||
format_user=StringFormatter(slots=["[INST] {{content}}[/INST]"]),
|
||
format_assistant=StringFormatter(slots=[" {{content}}", {"eos_token"}]),
|
||
format_function=FunctionFormatter(slots=["[TOOL_CALLS] ", "{{content}}", {"eos_token"}], tool_format="mistral"),
|
||
format_observation=StringFormatter(slots=["""[TOOL_RESULTS] {"content": {{content}}}[/TOOL_RESULTS]"""]),
|
||
format_tools=ToolFormatter(tool_format="mistral"),
|
||
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
|
||
mm_plugin=get_mm_plugin(name="llava_next", image_token="<image>"),
|
||
)
|
||
|
||
|
||
# copied from chatml template
|
||
_register_template(
|
||
name="llava_next_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_function=FunctionFormatter(slots=["{{content}}", "<|im_end|>"], tool_format="qwen"),
|
||
format_observation=StringFormatter(
|
||
slots=["<|im_start|>user\n<tool_response>\n{{content}}\n</tool_response><|im_end|>\n<|im_start|>assistant\n"]
|
||
),
|
||
format_tools=ToolFormatter(tool_format="qwen"),
|
||
format_separator=EmptyFormatter(slots=["\n"]),
|
||
default_system="You are a helpful assistant.",
|
||
stop_words=["<|im_end|>"],
|
||
replace_eos=True,
|
||
mm_plugin=get_mm_plugin(name="llava_next", image_token="<image>"),
|
||
)
|
||
|
||
|
||
# copied from chatml template
|
||
_register_template(
|
||
name="llava_next_yi",
|
||
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|>"],
|
||
replace_eos=True,
|
||
mm_plugin=get_mm_plugin(name="llava_next", image_token="<image>"),
|
||
)
|
||
|
||
|
||
# copied from vicuna template
|
||
_register_template(
|
||
name="llava_next_video",
|
||
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."
|
||
),
|
||
mm_plugin=get_mm_plugin(name="llava_next_video", image_token="<image>", video_token="<video>"),
|
||
)
|
||
|
||
|
||
# copied from mistral template
|
||
_register_template(
|
||
name="llava_next_video_mistral",
|
||
format_user=StringFormatter(slots=["[INST] {{content}}[/INST]"]),
|
||
format_assistant=StringFormatter(slots=[" {{content}}", {"eos_token"}]),
|
||
format_function=FunctionFormatter(slots=["[TOOL_CALLS] ", "{{content}}", {"eos_token"}], tool_format="mistral"),
|
||
format_observation=StringFormatter(slots=["""[TOOL_RESULTS] {"content": {{content}}}[/TOOL_RESULTS]"""]),
|
||
format_tools=ToolFormatter(tool_format="mistral"),
|
||
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
|
||
mm_plugin=get_mm_plugin(name="llava_next_video", image_token="<image>", video_token="<video>"),
|
||
)
|
||
|
||
|
||
# copied from chatml template
|
||
_register_template(
|
||
name="llava_next_video_yi",
|
||
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|>"],
|
||
replace_eos=True,
|
||
mm_plugin=get_mm_plugin(name="llava_next_video", image_token="<image>", video_token="<video>"),
|
||
)
|
||
|
||
|
||
# copied from chatml template
|
||
_register_template(
|
||
name="marco",
|
||
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_observation=StringFormatter(slots=["<|im_start|>tool\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
|
||
format_separator=EmptyFormatter(slots=["\n"]),
|
||
default_system=(
|
||
"你是一个经过良好训练的AI助手，你的名字是Marco-o1.由阿里国际数字商业集团的AI Business创造.\n## 重要！！！！！\n"
|
||
"当你回答问题时，你的思考应该在<Thought>内完成，<Output>内输出你的结果。\n"
|
||
"<Thought>应该尽可能是英文，但是有2个特例，一个是对原文中的引用，另一个是是数学应该使用markdown格式，<Output>内的输出需要遵循用户输入的语言。\n"
|
||
),
|
||
stop_words=["<|im_end|>"],
|
||
replace_eos=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="mistral",
|
||
format_user=StringFormatter(slots=["[INST] {{content}}[/INST]"]),
|
||
format_assistant=StringFormatter(slots=[" {{content}}", {"eos_token"}]),
|
||
format_function=FunctionFormatter(slots=["[TOOL_CALLS] ", "{{content}}", {"eos_token"}], tool_format="mistral"),
|
||
format_observation=StringFormatter(slots=["""[TOOL_RESULTS] {"content": {{content}}}[/TOOL_RESULTS]"""]),
|
||
format_tools=ToolFormatter(tool_format="mistral"),
|
||
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="olmo",
|
||
format_user=StringFormatter(slots=["<|user|>\n{{content}}<|assistant|>\n"]),
|
||
format_prefix=EmptyFormatter(slots=[{"eos_token"}]),
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="openchat",
|
||
format_user=StringFormatter(slots=["GPT4 Correct User: {{content}}", {"eos_token"}, "GPT4 Correct Assistant:"]),
|
||
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="openchat-3.6",
|
||
format_user=StringFormatter(
|
||
slots=[
|
||
(
|
||
"<|start_header_id|>GPT4 Correct User<|end_header_id|>\n\n{{content}}<|eot_id|>"
|
||
"<|start_header_id|>GPT4 Correct Assistant<|end_header_id|>\n\n"
|
||
)
|
||
]
|
||
),
|
||
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
|
||
stop_words=["<|eot_id|>"],
|
||
replace_eos=True,
|
||
)
|
||
|
||
|
||
# copied from chatml template
|
||
_register_template(
|
||
name="opencoder",
|
||
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_observation=StringFormatter(slots=["<|im_start|>tool\n{{content}}<|im_end|>\n<|im_start|>assistant\n"]),
|
||
format_separator=EmptyFormatter(slots=["\n"]),
|
||
default_system="You are OpenCoder, created by OpenCoder Team.",
|
||
stop_words=["<|im_end|>"],
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="orion",
|
||
format_user=StringFormatter(slots=["Human: {{content}}\n\nAssistant: ", {"eos_token"}]),
|
||
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
|
||
)
|
||
|
||
|
||
# copied from gemma template
|
||
_register_template(
|
||
name="paligemma",
|
||
format_user=StringFormatter(slots=["<start_of_turn>user\n{{content}}<end_of_turn>\n<start_of_turn>model\n"]),
|
||
format_observation=StringFormatter(
|
||
slots=["<start_of_turn>tool\n{{content}}<end_of_turn>\n<start_of_turn>model\n"]
|
||
),
|
||
format_separator=EmptyFormatter(slots=["<end_of_turn>\n"]),
|
||
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
|
||
efficient_eos=True,
|
||
mm_plugin=get_mm_plugin(name="paligemma", image_token="<image>"),
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="phi",
|
||
format_user=StringFormatter(slots=["<|user|>\n{{content}}<|end|>\n<|assistant|>\n"]),
|
||
format_system=StringFormatter(slots=["<|system|>\n{{content}}<|end|>\n"]),
|
||
format_separator=EmptyFormatter(slots=["\n"]),
|
||
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
|
||
stop_words=["<|end|>"],
|
||
replace_eos=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="phi_small",
|
||
format_user=StringFormatter(slots=["<|user|>\n{{content}}<|end|>\n<|assistant|>\n"]),
|
||
format_system=StringFormatter(slots=["<|system|>\n{{content}}<|end|>\n"]),
|
||
format_separator=EmptyFormatter(slots=["\n"]),
|
||
format_prefix=EmptyFormatter(slots=[{"<|endoftext|>"}]),
|
||
stop_words=["<|end|>"],
|
||
replace_eos=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="pixtral",
|
||
format_user=StringFormatter(slots=["[INST] {{content}} [/INST]"]),
|
||
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
|
||
mm_plugin=get_mm_plugin(name="pixtral", image_token="[IMG]"),
|
||
)
|
||
|
||
|
||
# copied from chatml template
|
||
_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_function=FunctionFormatter(slots=["{{content}}", "<|im_end|>"], tool_format="qwen"),
|
||
format_observation=StringFormatter(
|
||
slots=["<|im_start|>user\n<tool_response>\n{{content}}\n</tool_response><|im_end|>\n<|im_start|>assistant\n"]
|
||
),
|
||
format_tools=ToolFormatter(tool_format="qwen"),
|
||
format_separator=EmptyFormatter(slots=["\n"]),
|
||
default_system="You are a helpful assistant.",
|
||
stop_words=["<|im_end|>"],
|
||
)
|
||
|
||
|
||
# copied from chatml template
|
||
_register_template(
|
||
name="qwen2_vl",
|
||
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_function=FunctionFormatter(slots=["{{content}}", "<|im_end|>"], tool_format="qwen"),
|
||
format_observation=StringFormatter(
|
||
slots=["<|im_start|>user\n<tool_response>\n{{content}}\n</tool_response><|im_end|>\n<|im_start|>assistant\n"]
|
||
),
|
||
format_tools=ToolFormatter(tool_format="qwen"),
|
||
format_separator=EmptyFormatter(slots=["\n"]),
|
||
default_system="You are a helpful assistant.",
|
||
stop_words=["<|im_end|>"],
|
||
mm_plugin=get_mm_plugin(name="qwen2_vl", image_token="<|image_pad|>", video_token="<|video_pad|>"),
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="sailor",
|
||
format_user=StringFormatter(slots=["<|im_start|>question\n{{content}}<|im_end|>\n<|im_start|>answer\n"]),
|
||
format_system=StringFormatter(slots=["<|im_start|>system\n{{content}}<|im_end|>\n"]),
|
||
format_separator=EmptyFormatter(slots=["\n"]),
|
||
default_system=(
|
||
"You are an AI assistant named Sailor created by Sea AI Lab. "
|
||
"Your answer should be friendly, unbiased, faithful, informative and detailed."
|
||
),
|
||
stop_words=["<|im_end|>"],
|
||
)
|
||
|
||
|
||
# copied from llama3 template
|
||
_register_template(
|
||
name="skywork_o1",
|
||
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=["<|start_header_id|>system<|end_header_id|>\n\n{{content}}<|eot_id|>"]),
|
||
format_observation=StringFormatter(
|
||
slots=[
|
||
(
|
||
"<|start_header_id|>tool<|end_header_id|>\n\n{{content}}<|eot_id|>"
|
||
"<|start_header_id|>assistant<|end_header_id|>\n\n"
|
||
)
|
||
]
|
||
),
|
||
format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
|
||
default_system=(
|
||
"You are Skywork-o1, a thinking model developed by Skywork AI, specializing in solving complex problems "
|
||
"involving mathematics, coding, and logical reasoning through deep thought. When faced with a user's request, "
|
||
"you first engage in a lengthy and in-depth thinking process to explore possible solutions to the problem. "
|
||
"After completing your thoughts, you then provide a detailed explanation of the solution process "
|
||
"in your response."
|
||
),
|
||
stop_words=["<|eot_id|>"],
|
||
)
|
||
|
||
|
||
_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,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="telechat",
|
||
format_user=StringFormatter(slots=["<_user>{{content}}<_bot>"]),
|
||
format_system=StringFormatter(slots=["<_system>{{content}}<_end>"]),
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="telechat2",
|
||
format_user=StringFormatter(slots=["<_user>{{content}}<_bot>"]),
|
||
format_system=StringFormatter(slots=["<_system>{{content}}"]),
|
||
default_system=(
|
||
"你是中国电信星辰语义大模型，英文名是TeleChat，你是由中电信人工智能科技有限公司和中国电信人工智能研究院（TeleAI）研发的人工智能助手。"
|
||
),
|
||
)
|
||
|
||
|
||
_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."
|
||
),
|
||
replace_jinja_template=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="video_llava",
|
||
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."
|
||
),
|
||
mm_plugin=get_mm_plugin(name="video_llava", image_token="<image>", video_token="<video>"),
|
||
)
|
||
|
||
|
||
_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|>"],
|
||
)
|
||
|
||
|
||
# copied from chatml template
|
||
_register_template(
|
||
name="yi",
|
||
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|>"],
|
||
replace_eos=True,
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="yi_vl",
|
||
format_user=StringFormatter(slots=["### Human: {{content}}\n### Assistant:"]),
|
||
format_separator=EmptyFormatter(slots=["\n"]),
|
||
default_system=(
|
||
"This is a chat between an inquisitive human and an AI assistant. "
|
||
"Assume the role of the AI assistant. Read all the images carefully, "
|
||
"and respond to the human's questions with informative, helpful, detailed and polite answers. "
|
||
"这是一个好奇的人类和一个人工智能助手之间的对话。假设你扮演这个AI助手的角色。"
|
||
"仔细阅读所有的图像，并对人类的问题做出信息丰富、有帮助、详细的和礼貌的回答。\n\n"
|
||
),
|
||
stop_words=["###"],
|
||
efficient_eos=True,
|
||
mm_plugin=get_mm_plugin(name="llava", image_token="<image>"),
|
||
)
|
||
|
||
|
||
_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|>\n"]),
|
||
format_system=StringFormatter(slots=["<|system|>\n{{content}}", {"eos_token"}]),
|
||
default_system="You are Zephyr, a helpful assistant.",
|
||
)
|
||
|
||
|
||
_register_template(
|
||
name="ziya",
|
||
format_user=StringFormatter(slots=["<human>:{{content}}\n<bot>:"]),
|
||
format_separator=EmptyFormatter(slots=["\n"]),
|
||
)
|