Upload RedPajama-Data-1T-1024Sample.py

RedPajama-Data-1T-1024Sample.py

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+# Copyright 2023 Together Computer
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# Lint as: python3
+"""RedPajama: An Open-Source, Clean-Room 1.2 Trillion Token Dataset."""
+
+
+import json
+
+import datasets
+
+
+logger = datasets.logging.get_logger(__name__)
+
+
+_DESCRIPTION = """\
+RedPajama is a clean-room, fully open-source implementation of the LLaMa dataset. This is a 1B-token sample of the full dataset.
+"""
+
+_URLS = [
+    "arxiv_sample.jsonl",
+    "book_sample.jsonl",
+    "c4_sample.jsonl",
+    "cc_2019-30_sample.jsonl",
+    "cc_2020-05_sample.jsonl",
+    "cc_2021-04_sample.jsonl",
+    "cc_2022-05_sample.jsonl",
+    "cc_2023-06_sample.jsonl",
+    "github_sample.jsonl",
+    "stackexchange_sample.jsonl",
+    "wikipedia_sample.jsonl",
+]
+
+
+class RedPajama1TSampleConfig(datasets.BuilderConfig):
+    """BuilderConfig for RedPajama sample."""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig for RedPajama sample.
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(RedPajama1TSampleConfig, self).__init__(**kwargs)
+
+
+class RedPajama1TSample(datasets.GeneratorBasedBuilder):
+    """RedPajama 1T Sample: version 1.0.0."""
+
+    BUILDER_CONFIGS = [
+        RedPajama1TSampleConfig(
+            name="plain_text",
+            version=datasets.Version("1.0.0", ""),
+            description="Plain text",
+        ),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "text": datasets.Value("string"),
+                    "meta": datasets.Value("string"),
+                }
+            ),
+            supervised_keys=None,
+        )
+
+    def _split_generators(self, dl_manager):
+        downloaded_files = dl_manager.download_and_extract(_URLS)
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": downloaded_files})
+        ]
+
+    def _generate_examples(self, filepaths):
+        """This function returns the examples in the raw (text) form."""
+        logger.info("generating examples from = %s", filepaths)
+        key = 0
+        for filepath in filepaths:
+            with open(filepath, encoding="utf-8") as f:
+                for row in f:
+                    data = json.loads(row)
+                    if "meta" not in data:
+                        text = data["text"]
+                        del data["text"]
+                        yield key, {
+                            "text": text,
+                            "meta": json.dumps(data),
+                        }
+                    else:
+                        yield key, {
+                            "text": data["text"],
+                            "meta": data["meta"],
+                        }
+                    key += 1