Long context datasets

model/model_training/custom_datasets/__init__.py

@@ -5,7 +5,12 @@
 
 import numpy as np
 from model_training.custom_datasets.extra_rm_datasets import load_anthropic_rlhf, load_hellaswag, load_shp
-from model_training.custom_datasets.instruction import INSTRUCTION_DATASETS, InstructionDataset
+from model_training.custom_datasets.instruction import (
+    INSTRUCTION_DATASETS,
+    RAG_DATASETS,
+    InstructionDataset,
+    RAGDataset,
+)
 from model_training.custom_datasets.oasst_dataset import load_oasst_export
 from model_training.custom_datasets.pretrain_datasets import FanFics, RedPajama
 from model_training.custom_datasets.prompt_dialogue import DolphinMix, Gpt4All, OrcaChat, load_oig_file
@@ -181,6 +186,8 @@ def get_one_dataset(
         dataset = OrcaChat(cache_dir=data_path, **kwargs)
     elif dataset_name == "dolphin-mix":
         dataset = DolphinMix(cache_dir=data_path, **kwargs)
+    elif dataset_name in RAG_DATASETS.keys():
+        dataset = RAGDataset(dataset_name, cache_dir=data_path, **kwargs)
     else:
         raise ValueError(f"Unknown dataset {dataset_name}")
 

model/model_training/custom_datasets/instruction.py

@@ -124,3 +124,32 @@ def __getitem__(self, idx) -> DatasetEntry:
             answers=answers,
             lang=lang,
         )
+
+
+RAG_DATASETS = {
+    "multi-chapter-summaries": "shahules786/Multi-chapter-summaries",
+}
+
+
+class RAGDataset(Dataset):
+    def __init__(
+        self,
+        dataset,
+        split: str = "train",
+        cache_dir: str = ".cache/",
+    ):
+        if dataset not in RAG_DATASETS.keys():
+            raise ValueError(f"Invalid dataset {dataset}")
+
+        if dataset == "multi-chapter-summaries":
+            self.prompt, self.context, self.response = "prompt", "context", "response"
+
+        self.dataset = load_dataset(RAG_DATASETS[dataset], cache_dir=cache_dir)[split]
+
+    def __len__(self):
+        return len(self.dataset)
+
+    def __getitem__(self, idx):
+        prompt, context, response = [self.dataset[idx][key] for key in [self.prompt, self.context, self.response]]
+
+        return create_dataset_entry_qa(mode="sft", questions=[prompt + context], answers=[response])