simplify readme

Former-commit-id: 0da6ec2d516326fe9c7583ba71cd1778eb838178

src/llmtuner/train/rm/collator.py

@@ -1,29 +0,0 @@
-from dataclasses import dataclass
-from typing import Any, Dict, Sequence
-
-import torch
-from transformers import DataCollatorWithPadding
-
-
-@dataclass
-class PairwiseDataCollatorWithPadding(DataCollatorWithPadding):
-    r"""
-    Data collator for pairwise data.
-    """
-
-    def __call__(self, features: Sequence[Dict[str, Any]]) -> Dict[str, torch.Tensor]:
-        r"""
-        Pads batched data to the longest sequence in the batch.
-
-        We generate 2 * n examples where the first n examples represent chosen examples and
-        the last n examples represent rejected examples.
-        """
-        features = [
-            {
-                "input_ids": feature["prompt_ids"] + feature[key],
-                "attention_mask": [1] * (len(feature["prompt_ids"]) + len(feature[key])),
-            }
-            for key in ("chosen_ids", "rejected_ids")
-            for feature in features
-        ]
-        return super().__call__(features)