Add v1 files and loading script

.gitattributes

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-*.bin.* filter=lfs diff=lfs merge=lfs -text
-*.lfs.* filter=lfs diff=lfs merge=lfs -text
-*.bin filter=lfs diff=lfs merge=lfs -text
-*.h5 filter=lfs diff=lfs merge=lfs -text
-*.tflite filter=lfs diff=lfs merge=lfs -text
-*.tar.gz filter=lfs diff=lfs merge=lfs -text
-*.ot filter=lfs diff=lfs merge=lfs -text
-*.onnx filter=lfs diff=lfs merge=lfs -text
-*.arrow filter=lfs diff=lfs merge=lfs -text
-*.ftz filter=lfs diff=lfs merge=lfs -text
-*.joblib filter=lfs diff=lfs merge=lfs -text
-*.model filter=lfs diff=lfs merge=lfs -text
-*.msgpack filter=lfs diff=lfs merge=lfs -text
-*.pb filter=lfs diff=lfs merge=lfs -text
-*.pt filter=lfs diff=lfs merge=lfs -text
-*.pth filter=lfs diff=lfs merge=lfs -text
+personachat_truecased_full_train.json filter=lfs diff=lfs merge=lfs -text
+personachat_truecased_full_valid.json filter=lfs diff=lfs merge=lfs -text
+personachat_truecased_sample_train.json filter=lfs diff=lfs merge=lfs -text
+personachat_truecased_sample_valid.json filter=lfs diff=lfs merge=lfs -text
+dataset_infos.json filter=lfs diff=lfs merge=lfs -text

.gitignore

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+venv
+.idea

personachat_truecased.py

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+import json
+
+import datasets
+from datasets.features import Sequence
+
+
+_BASE_URL = "https://huggingface.co/datasets/bavard/personachat_truecased/raw/main"
+_URLS = {
+    "full": {
+        "train": _BASE_URL + "/persona_chat_truecased_full_train.json",
+        "valid": _BASE_URL + "/persona_chat_truecased_full_valid.json"
+    },
+    "sample": {
+        "train": _BASE_URL + "/persona_chat_truecased_sample_train.json",
+        "valid": _BASE_URL + "/persona_chat_truecased_sample_valid.json"
+    }
+}
+
+_DESCRIPTION = """\
+A version of the PersonaChat dataset that has been true-cased, and also has been given more normalized punctuation.
+The original PersonaChat dataset is in all lower case, and has extra space around each clause/sentence separating
+punctuation mark. This version of the dataset has more of a natural language look, with sentence capitalization,
+proper noun capitalization, and normalized whitespace. Also, each dialogue turn includes a pool of distractor
+candidate responses, which can be used by a multiple choice regularization loss during training.
+"""
+
+_CITATION = """\
+@article{zhang2018personalizing,
+  title={Personalizing dialogue agents: I have a dog, do you have pets too?},
+  author={Zhang, Saizheng and Dinan, Emily and Urbanek, Jack and Szlam, Arthur and Kiela, Douwe and Weston, Jason},
+  journal={arXiv preprint arXiv:1801.07243},
+  year={2018}
+}
+"""
+
+
+class PersonachatTruecased(datasets.DatasetBuilder):
+    """
+    Version of the PersonaChat dataset that includes true-casing, normalized punctuation, and candidate distractor
+    responses for each dialogue turn, for including a multiple choice regularzation loss while training.
+    """
+
+    VERSION = datasets.Version("1.0.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="full", version=VERSION, description="The full dataset."),
+        datasets.BuilderConfig(name="sample", version=VERSION, description="A sample sample of the dataset, useful for testing.")
+    ]
+
+    DEFAULT_CONFIG_NAME = "full"
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features({
+                "personality": Sequence(datasets.Value("string")),
+                "candidates": Sequence(datasets.Value("string")),
+                "history": Sequence(datasets.Value("string")),
+                "conv_id": datasets.Value("int32"),
+                "utterance_idx": datasets.Value("int32")
+            }),
+            citation=_CITATION
+        )
+
+    def _split_generators(self, dl_manager: datasets.DownloadManager):
+        split_paths = dl_manager.download(_URLS[self.config.name])
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={"data_path": split_paths["train"]}
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"data_path": split_paths["valid"]}
+            )
+        ]
+
+    def _generate_examples(self, data_path: str):
+        with open(data_path) as f:
+            data = json.load(f)
+        for conv_id, conv in enumerate(data):
+            personality = conv["personality"]
+            for utterance_idx, utterance in enumerate(conv["utterances"]):
+                id_ = f"{conv_id}-{utterance_idx}"
+                yield id_, {
+                    "personality": personality,
+                    "candidates": utterance["candidates"],
+                    "history": utterance["history"],
+                    "conv_id": conv_id,
+                    "utterance_idx": utterance_idx
+                }

personachat_truecased_full_train.json

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+size 193210313

personachat_truecased_full_valid.json

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+oid sha256:2277648a4b773d81cf3406eb872deff9489a930c7140b5a1a1bed79a48317562
+size 11995403

personachat_truecased_sample_train.json

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+oid sha256:cba1d219748010a15e47bdb5fbc78903bd77c52ffa2ff8fdb96e6e68d1747e5a
+size 21396

personachat_truecased_sample_valid.json

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+size 23092