Update files from the datasets library (from 1.2.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.2.0

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bin.* filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet 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
+*.rar filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+annotations_creators:
+- expert-generated
+- machine-generated
+language_creators:
+- found
+- expert-generated
+languages:
+- th
+licenses:
+- cc-by-3-0
+multilinguality:
+- monolingual
+size_categories:
+- 1k<n<10k
+source_datasets:
+- extended|other-tirasaroj-aroonmanakun
+task_categories:
+- structure-prediction
+task_ids:
+- named-entity-recognition
+- parsing
+---
+
+# Dataset Card for `thainer`
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-instances)
+  - [Data Splits](#data-instances)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** https://github.com/wannaphong/thai-ner
+- **Repository:** https://github.com/wannaphong/thai-ner
+- **Paper:**
+- **Leaderboard:**
+- **Point of Contact:** https://github.com/wannaphong/
+
+### Dataset Summary
+
+ThaiNER (v1.3) is a 6,456-sentence named entity recognition dataset created from expanding the 2,258-sentence [unnamed dataset](http://pioneer.chula.ac.th/~awirote/Data-Nutcha.zip) by [Tirasaroj and Aroonmanakun (2012)](http://pioneer.chula.ac.th/~awirote/publications/). It is used to train NER taggers in [PyThaiNLP](https://github.com/PyThaiNLP/pythainlp). The NER tags are annotated by [Tirasaroj and Aroonmanakun (2012)]((http://pioneer.chula.ac.th/~awirote/publications/)) for 2,258 sentences and the rest by [@wannaphong](https://github.com/wannaphong/). The POS tags are done by [PyThaiNLP](https://github.com/PyThaiNLP/pythainlp)'s `perceptron` engine trained on `orchid_ud`. [@wannaphong](https://github.com/wannaphong/) is now the only maintainer of this dataset.
+
+### Supported Tasks and Leaderboards
+
+- named entity recognition
+- pos tagging
+
+### Languages
+
+Thai
+
+## Dataset Structure
+
+### Data Instances
+
+```
+{'id': 100, 'ner_tags': [27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27], 'pos_tags': [6, 12, 13, 1, 6, 5, 11, 7, 11, 6, 5, 13, 6, 6, 6, 11, 6, 6, 11, 6, 6, 11, 6, 6, 13, 6, 11, 11, 6, 11, 6, 11, 6, 11, 6, 11, 11, 6, 6, 11, 12, 6, 13, 5, 11, 7, 11, 6, 3, 11, 12, 3, 13, 6, 1, 6, 12, 13, 1, 6, 6, 5, 11, 3, 11, 5, 4, 6, 13, 6, 13, 6, 10, 3, 13, 13, 12, 13, 12, 0, 1, 10, 11, 6, 6, 11, 6, 11, 6, 12, 13, 5, 12, 3, 13, 13, 1, 6, 1, 6, 13], 'tokens': ['เชื้อโรค', 'ที่', 'ปรากฏ', 'ใน', 'สัตว์', 'ทั้ง', ' ', '4', ' ', 'ชนิด', 'นี้', 'เป็น', 'เชื้อ', 'โรคไข้หวัด', 'นก', ' ', 'เอช', 'พี', ' ', 'เอ', 'เวียน', ' ', 'อิน', 'ฟลู', 'เอน', 'ซา', ' ', '(', 'Hight', ' ', 'Polygenic', ' ', 'Avain', ' ', 'Influenza', ')', ' ', 'ชนิด', 'รุนแรง', ' ', 'ซึ่ง', 'การ', 'ตั้งชื่อ', 'ทั้ง', ' ', '4', ' ', 'ขึ้น', 'มา', ' ', 'เพื่อที่จะ', 'สามารถ', 'ระบุ', 'เชื้อ', 'ของ', 'ไวรัส', 'ที่', 'ทำอันตราย', 'ตาม', 'สิ่งมีชีวิต', 'ประเภท', 'ต่างๆ', ' ', 'ได้', ' ', 'อีก', 'ทั้ง', 'การ', 'ระบุ', 'สถานที่', 'คือ', 'ประเทศ', 'ไทย', 'จะ', 'ทำให้', 'รู้', 'ว่า', 'พบ', 'ที่', 'แรก', 'ใน', 'ไทย', ' ', 'ส่วน', 'วัน', ' ', 'เดือน', ' ', 'ปี', 'ที่', 'พบ', 'นั้น', 'ก็', 'จะ', 'ทำให้', 'ทราบ', 'ถึง', 'ครั้งแรก', 'ของ', 'การ', 'ค้นพบ']}
+{'id': 107, 'ner_tags': [27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27], 'pos_tags': [0, 1, 6, 5, 11, 12, 3, 3, 13, 6, 13, 12, 0, 2, 12, 11, 6, 5, 13, 6, 5, 1, 6, 6, 1, 10, 11, 4, 13, 6, 11, 12, 6, 6, 10, 11, 13, 6, 1, 6, 4, 6, 1, 6, 6, 11, 4, 6, 1, 5, 6, 12, 2, 13, 6, 6, 5, 1, 11, 12, 13, 1, 6, 6, 11, 13, 11, 6, 6, 6, 11, 11, 6, 11, 11, 4, 10, 11, 11, 6, 11], 'tokens': ['ล่าสุด', 'ใน', 'เรื่อง', 'นี้', ' ', 'ทั้งนี้', 'คง', 'ต้อง', 'มี', 'การ', 'ตรวจสอบ', 'ให้', 'ชัดเจน', 'อีกครั้ง', 'ว่า', ' ', 'ไวรัส', 'นี้', 'เป็น', 'ชนิด', 'เดียว', 'กับ', 'ไข้หวัด', 'นก', 'ใน', 'ไทย', ' ', 'หรือ', 'เป็น', 'การกลายพันธุ์', ' ', 'โดยที่', 'คณะ', 'สัตวแพทย์', 'มหาวิทยาลัยเกษตรศาสตร์', ' ', 'จัด', 'ระดมสมอง', 'จาก', 'คณบดี', 'และ', 'ผู้เชี่ยวชาญ', 'จาก', 'คณะ', 'สัตวแพทย์', ' ', 'และ', 'ปศุสัตว์', 'ของ', 'หลาย', 'มหาวิทยาลัย', 'เพื่อ', 'ร่วมกัน', 'หา', 'ข้อมูล', 'เรื่อง', 'นี้', 'ด้วย', ' ', 'โดย', 'ประสาน', 'กับ', 'เจ้าหน้าที่', 'ระหว่างประเทศ', ' ', 'คือ', ' ', 'องค์การ', 'สุขภาพ', 'สัตว์โลก', ' ', '(', 'OIE', ')', ' ', 'และ', 'องค์การอนามัยโลก', ' ', '(', 'WHO', ')']}
+```
+
+### Data Fields
+
+- `id`: sentence id
+- `tokens`: word tokens by [PyThaiNLP](https://github.com/PyThaiNLP/pythainlp)'s dictionary-based tokenizer `newmm`
+- `pos_tags`: POS tags tagged by [PyThaiNLP](https://github.com/PyThaiNLP/pythainlp)'s `perceptron` engine trained on `orchid_ud`
+- `ner_tags`: NER tags tagged by humans
+
+### Data Splits
+
+No explicit split is given
+
+## Dataset Creation
+
+### Curation Rationale
+
+ThaiNER (v1.3) is a 6,456-sentence named entity recognition dataset created from expanding the 2,258-sentence [unnamed dataset](http://pioneer.chula.ac.th/~awirote/Data-Nutcha.zip) by [Tirasaroj and Aroonmanakun (2012)](http://pioneer.chula.ac.th/~awirote/publications/). It is used to train NER taggers in [PyThaiNLP](https://github.com/PyThaiNLP/pythainlp). 
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+The earlier part of the dataset is all news articles, whereas the part added by [@wannaphong](https://github.com/wannaphong/) includes news articles, public announcements and [@wannaphong](https://github.com/wannaphong/)'s own chat messages with personal and sensitive information removed.
+
+#### Who are the source language producers?
+
+News articles and public announcements are created by their respective authors. Chat messages are created by [@wannaphong](https://github.com/wannaphong/).
+
+### Annotations
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[Tirasaroj and Aroonmanakun (2012)](http://pioneer.chula.ac.th/~awirote/publications/) for the earlier 2,258 sentences and [@wannaphong](https://github.com/wannaphong/) for the rest
+
+### Personal and Sensitive Information
+
+News articles and public announcements are not expected to include personal and sensitive information. [@wannaphong](https://github.com/wannaphong/) has removed such information from his own chat messages.
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+- named entity recognition in Thai
+
+### Discussion of Biases
+
+Since almost all of collection and annotation is done by [@wannaphong](https://github.com/wannaphong/), his biases are expected to be reflected in the dataset.
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+[Tirasaroj and Aroonmanakun (2012)](http://pioneer.chula.ac.th/~awirote/publications/) for the earlier 2,258 sentences and [@wannaphong](https://github.com/wannaphong/) for the rest
+
+### Licensing Information
+
+CC-BY 3.0
+
+### Citation Information
+
+```
+@misc{Wannaphong Phatthiyaphaibun_2019,
+    title={wannaphongcom/thai-ner: ThaiNER 1.3},
+    url={https://zenodo.org/record/3550546},
+    DOI={10.5281/ZENODO.3550546},
+    abstractNote={Thai Named Entity Recognition},
+    publisher={Zenodo},
+    author={Wannaphong Phatthiyaphaibun},
+    year={2019},
+    month={Nov}
+}
+```
+
+Work extended from:
+[Tirasaroj, N.  and Aroonmanakun, W. 2012. Thai NER using CRF model based on surface features. In Proceedings of SNLP-AOS 2011, 9-10 February, 2012, Bangkok, pages 176-180.](http://pioneer.chula.ac.th/~awirote/publications/)

dataset_infos.json

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+{"thainer": {"description": "ThaiNER (v1.3) is a 6,456-sentence named entity recognition dataset created from expanding the 2,258-sentence\n[unnamed dataset](http://pioneer.chula.ac.th/~awirote/Data-Nutcha.zip) by\n[Tirasaroj and Aroonmanakun (2012)](http://pioneer.chula.ac.th/~awirote/publications/).\nIt is used to train NER taggers in [PyThaiNLP](https://github.com/PyThaiNLP/pythainlp).\nThe NER tags are annotated by [Tirasaroj and Aroonmanakun (2012)]((http://pioneer.chula.ac.th/~awirote/publications/))\nfor 2,258 sentences and the rest by [@wannaphong](https://github.com/wannaphong/).\nThe POS tags are done by [PyThaiNLP](https://github.com/PyThaiNLP/pythainlp)'s `perceptron` engine trained on `orchid_ud`.\n[@wannaphong](https://github.com/wannaphong/) is now the only maintainer of this dataset.\n", "citation": "@misc{Wannaphong Phatthiyaphaibun_2019,\n    title={wannaphongcom/thai-ner: ThaiNER 1.3},\n    url={https://zenodo.org/record/3550546},\n    DOI={10.5281/ZENODO.3550546},\n    abstractNote={Thai Named Entity Recognition},\n    publisher={Zenodo},\n    author={Wannaphong Phatthiyaphaibun},\n    year={2019},\n    month={Nov}\n}\n", "homepage": "https://github.com/wannaphong/thai-ner/", "license": "CC-BY 3.0", "features": {"id": {"dtype": "int32", "id": null, "_type": "Value"}, "tokens": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "pos_tags": {"feature": {"num_classes": 14, "names": ["ADJ", "ADP", "ADV", "AUX", "CCONJ", "DET", "NOUN", "NUM", "PART", "PRON", "PROPN", "PUNCT", "SCONJ", "VERB"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}, "ner_tags": {"feature": {"num_classes": 28, "names": ["B-DATE", "B-EMAIL", "B-LAW", "B-LEN", "B-LOCATION", "B-MONEY", "B-ORGANIZATION", "B-PERCENT", "B-PERSON", "B-PHONE", "B-TIME", "B-URL", "B-ZIP", "B-\u0e44\u0e21\u0e48\u0e22\u0e37\u0e19\u0e22\u0e31\u0e19", "I-DATE", "I-EMAIL", "I-LAW", "I-LEN", "I-LOCATION", "I-MONEY", "I-ORGANIZATION", "I-PERCENT", "I-PERSON", "I-PHONE", "I-TIME", "I-URL", "I-\u0e44\u0e21\u0e48\u0e22\u0e37\u0e19\u0e22\u0e31\u0e19", "O"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "thainer", "config_name": "thainer", "version": {"version_str": "1.3.0", "description": null, "major": 1, "minor": 3, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 8117918, "num_examples": 6349, "dataset_name": "thainer"}}, "download_checksums": {"https://github.com/wannaphong/thai-ner/raw/master/model/1.3/data-pos.conll": {"num_bytes": 5456461, "checksum": "be9f897b409554f06501c3a26159115fce5140d5654c634276b1a40b8c4dbabd"}}, "download_size": 5456461, "post_processing_size": null, "dataset_size": 8117918, "size_in_bytes": 13574379}}

dummy/thainer/1.3.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:da0ca6a2ed4db856ce0b018a96ea09432b93913f5a562642dee9616d7043f452
+size 1731

thainer.py

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+from __future__ import absolute_import, division, print_function
+
+import datasets
+
+
+_CITATION = """\
+@misc{Wannaphong Phatthiyaphaibun_2019,
+    title={wannaphongcom/thai-ner: ThaiNER 1.3},
+    url={https://zenodo.org/record/3550546},
+    DOI={10.5281/ZENODO.3550546},
+    abstractNote={Thai Named Entity Recognition},
+    publisher={Zenodo},
+    author={Wannaphong Phatthiyaphaibun},
+    year={2019},
+    month={Nov}
+}
+"""
+
+_LICENSE = "CC-BY 3.0"
+
+_DESCRIPTION = """\
+ThaiNER (v1.3) is a 6,456-sentence named entity recognition dataset created from expanding the 2,258-sentence
+[unnamed dataset](http://pioneer.chula.ac.th/~awirote/Data-Nutcha.zip) by
+[Tirasaroj and Aroonmanakun (2012)](http://pioneer.chula.ac.th/~awirote/publications/).
+It is used to train NER taggers in [PyThaiNLP](https://github.com/PyThaiNLP/pythainlp).
+The NER tags are annotated by [Tirasaroj and Aroonmanakun (2012)]((http://pioneer.chula.ac.th/~awirote/publications/))
+for 2,258 sentences and the rest by [@wannaphong](https://github.com/wannaphong/).
+The POS tags are done by [PyThaiNLP](https://github.com/PyThaiNLP/pythainlp)'s `perceptron` engine trained on `orchid_ud`.
+[@wannaphong](https://github.com/wannaphong/) is now the only maintainer of this dataset.
+"""
+
+
+class ThaiNerConfig(datasets.BuilderConfig):
+    """BuilderConfig for ThaiNer."""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig for ThaiNer.
+
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(ThaiNerConfig, self).__init__(**kwargs)
+
+
+class Thainer(datasets.GeneratorBasedBuilder):
+
+    _DOWNLOAD_URL = "https://github.com/wannaphong/thai-ner/raw/master/model/1.3/data-pos.conll"
+    _SENTENCE_SPLITTERS = ["", " ", "\n"]
+    _POS_TAGS = [
+        "ADJ",
+        "ADP",
+        "ADV",
+        "AUX",
+        "CCONJ",
+        "DET",
+        "NOUN",
+        "NUM",
+        "PART",
+        "PRON",
+        "PROPN",
+        "PUNCT",
+        "SCONJ",
+        "VERB",
+    ]
+    _NER_TAGS = [
+        "B-DATE",
+        "B-EMAIL",
+        "B-LAW",
+        "B-LEN",
+        "B-LOCATION",
+        "B-MONEY",
+        "B-ORGANIZATION",
+        "B-PERCENT",
+        "B-PERSON",
+        "B-PHONE",
+        "B-TIME",
+        "B-URL",
+        "B-ZIP",
+        "B-ไม่ยืนยัน",
+        "I-DATE",
+        "I-EMAIL",
+        "I-LAW",
+        "I-LEN",
+        "I-LOCATION",
+        "I-MONEY",
+        "I-ORGANIZATION",
+        "I-PERCENT",
+        "I-PERSON",
+        "I-PHONE",
+        "I-TIME",
+        "I-URL",
+        "I-ไม่ยืนยัน",
+        "O",
+    ]
+
+    BUILDER_CONFIGS = [
+        ThaiNerConfig(
+            name="thainer",
+            version=datasets.Version("1.3.0"),
+            description="Thai Named Entity Recognition for PyThaiNLP (6,456 sentences)",
+        ),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("int32"),
+                    "tokens": datasets.Sequence(datasets.Value("string")),
+                    "pos_tags": datasets.Sequence(datasets.features.ClassLabel(names=self._POS_TAGS)),
+                    "ner_tags": datasets.Sequence(datasets.features.ClassLabel(names=self._NER_TAGS)),
+                }
+            ),
+            supervised_keys=None,
+            homepage="https://github.com/wannaphong/thai-ner/",
+            citation=_CITATION,
+            license=_LICENSE,
+        )
+
+    def _split_generators(self, dl_manager):
+        data_path = dl_manager.download_and_extract(self._DOWNLOAD_URL)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"filepath": data_path},
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        with open(filepath, encoding="utf-8") as f:
+            guid = 0
+            tokens = []
+            pos_tags = []
+            ner_tags = []
+
+            for line in f:
+                if line in self._SENTENCE_SPLITTERS:
+                    if tokens:
+                        yield guid, {
+                            "id": str(guid),
+                            "tokens": tokens,
+                            "pos_tags": pos_tags,
+                            "ner_tags": ner_tags,
+                        }
+                        guid += 1
+                        tokens = []
+                        pos_tags = []
+                        ner_tags = []
+                else:
+                    # thainer tokens are tab separated
+                    splits = line.split("\t")
+                    # replace junk ner tags
+                    ner_tag = splits[2] if splits[2] in self._NER_TAGS else "O"
+                    tokens.append(splits[0])
+                    pos_tags.append(splits[1])
+                    ner_tags.append(ner_tag.rstrip())
+            # last example
+            yield guid, {
+                "id": str(guid),
+                "tokens": tokens,
+                "pos_tags": pos_tags,
+                "ner_tags": ner_tags,
+            }