Lint alpaca_chat

src/axolotl/prompt_strategies/alpaca_chat.py

@@ -1,3 +1,6 @@
+"""Module containing the AlpacaQAPromptTokenizingStrategy class"""
+
+from typing import Tuple
 from axolotl.prompt_tokenizers import (
     AlpacaPromptTokenizingStrategy,
     InstructionPromptTokenizingStrategy,
@@ -7,7 +10,7 @@ from axolotl.prompters import AlpacaPrompter, PromptStyle
 
 def load(tokenizer, cfg):
     return AlpacaPromptTokenizingStrategy(
-        AlpacaPrompter(PromptStyle.chat.value),
+        AlpacaPrompter(PromptStyle.CHAT.value),
         tokenizer,
         cfg.train_on_inputs,
         cfg.sequence_len,
@@ -15,7 +18,11 @@ def load(tokenizer, cfg):
 
 
 class AlpacaQAPromptTokenizingStrategy(InstructionPromptTokenizingStrategy):
-    def parse_instruction_fields(self, prompt) -> (str, str, str):
+    """
+    Tokenizing strategy for AlpacaQA
+    """
+
+    def parse_instruction_fields(self, prompt) -> Tuple[str, str, str]:
         return (
             prompt["question"],
             "",
@@ -25,7 +32,7 @@ class AlpacaQAPromptTokenizingStrategy(InstructionPromptTokenizingStrategy):
 
 def load_qa(tokenizer, cfg):
     return AlpacaQAPromptTokenizingStrategy(
-        AlpacaPrompter(PromptStyle.chat.value),
+        AlpacaPrompter(PromptStyle.CHAT.value),
         tokenizer,
         cfg.train_on_inputs,
         cfg.sequence_len,