Remove loading script, update README with yaml

README.md

@@ -1,3 +1,13 @@
+---
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: "train_chunked.jsonl"
+  - split: test
+    path: "test_chunked.jsonl"
+---
+
 # MathPile ArXiv (subset) 
 
 ## Description

mathpile_arxiv_subset_tiny.py

@@ -1,126 +0,0 @@
-# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
-#
-# 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.
-"""This dataset consists of a toy subset of 8834 (5000 training + 3834 testing) TeX files found in the arXiv subset of MathPile, used for testing. Each document is split using LaTeX-specific characters for recursive character text splitting with ~4k token window and ~1.5k token overlaps. You should not use this dataset. Training and testing sets are already split."""
-
-import json
-import os
-
-import datasets
-
-_CITATION = """\
-@article{wang2023mathpile,
-  title={Generative AI for Math: Part I -- MathPile: A Billion-Token-Scale Pretraining Corpus for Math},
-  author={Wang, Zengzhi and Xia, Rui and Liu, Pengfei},
-  journal={arXiv preprint arXiv:2312.17120},
-  year={2023}
-}
-"""
-
-_DESCRIPTION = """\
-This dataset consists of a toy subset of 8834 (5000 training + 3834 testing) TeX files found in the arXiv subset of MathPile, used for testing. Each document is split using LaTeX-specific characters for recursive character text splitting with ~4k token window and ~1.5k token overlaps. You should not use this dataset.
-"""
-
-_HOMEPAGE = "https://huggingface.co/datasets/aluncstokes/mathpile_arxiv_subset_tiny"
-
-
-_LICENSE = "CC BY-NC-SA 4.0"
-
-# The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
-# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
-_URLS = {"first_domain": "https://huggingface.co/datasets/GAIR/MathPile"}
-
-
-class MathpileArxivSubsetTiny(datasets.GeneratorBasedBuilder):
-    """This dataset consists of a toy subset of 8834 (5000 training + 3834 testing) TeX files found in the arXiv subset of MathPile, used for testing. Each document is split using LaTeX-specific characters for recursive character text splitting with ~4k token window and ~1.5k token overlaps. You should not use this dataset"""
-
-    VERSION = datasets.Version("0.2")
-
-    # This is an example of a dataset with multiple configurations.
-    # If you don't want/need to define several sub-sets in your dataset,
-    # just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes.
-
-    # If you need to make complex sub-parts in the datasets with configurable options
-    # You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig
-    # BUILDER_CONFIG_CLASS = MyBuilderConfig
-
-    # You will be able to load one or the other configurations in the following list with
-    # data = datasets.load_dataset('my_dataset', 'first_domain')
-    # data = datasets.load_dataset('my_dataset', 'second_domain')
-
-    DEFAULT_CONFIG_NAME = ""  # It's not mandatory to have a default configuration. Just use one if it make sense.
-
-    def _info(self):
-        if self.config.name == "":
-            features = datasets.Features(
-                {
-                    "set": datasets.Value("string"),
-                    "id": datasets.Value("string"),
-                    "chunk_text": datasets.Value("long_string"),
-                    "chunk_num_tokens": datasets.Value("uint32"),
-                    "document_num_tokens": datasets.Value("uint32"),
-                    "document_language": datasets.Value("string"),
-                }
-            )
-
-        return datasets.DatasetInfo(
-            # This is the description that will appear on the datasets page.
-            description=_DESCRIPTION,
-            # This defines the different columns of the dataset and their types
-            features=features,  # Here we define them above because they are different between the two configurations
-            # If there's a common (input, target) tuple from the features, uncomment supervised_keys line below and
-            # specify them. They'll be used if as_supervised=True in builder.as_dataset.
-            # supervised_keys=("sentence", "label"),
-            # Homepage of the dataset for documentation
-            homepage=_HOMEPAGE,
-            # License for the dataset if available
-            license=_LICENSE,
-            # Citation for the dataset
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name
-
-        # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS
-        # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
-        # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
-        urls = _URLS[self.config.name]
-        data_dir = dl_manager.download_and_extract(urls)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, "train_chunked.jsonl"),
-                    "split": "train",
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, "test_chunked.jsonl"),
-                    "split": "test",
-                },
-            ),
-        ]
-
-    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
-    def generate_examples(self, filepath, split):
-        # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
-        with open(filepath, encoding="utf-8") as f:
-            for key, row in enumerate(f):
-                data = json.loads(row)
-                # Yields examples as (key, example) tuples
-                yield key, {"text": data["chunk_text"]}