File size: 2,220 Bytes
8cc0aad 37293dc ce34d64 4ea9a66 8cc0aad ce34d64 4ea9a66 3a50377 4ac9e25 3a50377 8cc0aad 3a50377 4ac9e25 59bb219 4ac9e25 3a50377 8cc0aad ce34d64 3a50377 4ac9e25 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 |
"""Module containing the AlpacaQAPromptTokenizingStrategy class"""
from typing import Tuple
from axolotl.prompt_tokenizers import (
AlpacaPromptTokenizingStrategy,
InstructionPromptTokenizingStrategy,
)
from axolotl.prompters import AlpacaPrompter, PromptStyle
def load(tokenizer, cfg):
return AlpacaPromptTokenizingStrategy(
AlpacaPrompter(PromptStyle.CHAT.value),
tokenizer,
cfg.train_on_inputs,
cfg.sequence_len,
)
class AlpacaConcisePrompter(AlpacaPrompter):
"""
Alpaca Prompter extending the system prompt to ask for concise answers
"""
system_prompt = "Below is an instruction that describes a task, paired with an input that provides further context. Write a response that concisely and appropriately completes the request.\n\n"
system_no_input_prompt = "Below is an instruction that describes a task. Write a response that appropriately and concisely completes the request.\n\n"
class AlpacaQAPromptTokenizingStrategy(InstructionPromptTokenizingStrategy):
"""
Tokenizing strategy for AlpacaQA
"""
def parse_instruction_fields(self, prompt) -> Tuple[str, str, str]:
return (
prompt["question"],
"",
prompt["answer"],
)
class CamelAIPromptTokenizingStrategy(InstructionPromptTokenizingStrategy):
"""
Tokenizing strategy for CamelAI datasets
"""
def parse_instruction_fields(self, prompt) -> Tuple[str, str, str]:
return (
prompt["message_1"],
"",
prompt["message_2"],
)
def load_concise(tokenizer, cfg):
return AlpacaPromptTokenizingStrategy(
AlpacaConcisePrompter(PromptStyle.CHAT.value),
tokenizer,
cfg.train_on_inputs,
cfg.sequence_len,
)
def load_qa(tokenizer, cfg):
return AlpacaQAPromptTokenizingStrategy(
AlpacaPrompter(PromptStyle.CHAT.value),
tokenizer,
cfg.train_on_inputs,
cfg.sequence_len,
)
def load_camel_ai(tokenizer, cfg):
return CamelAIPromptTokenizingStrategy(
AlpacaPrompter(PromptStyle.CHAT.value),
tokenizer,
cfg.train_on_inputs,
cfg.sequence_len,
)
|