Update files from the datasets library (from 1.2.0)

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

.gitattributes

@@ -0,0 +1,27 @@
+*.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
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zstandard filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,145 @@
+---
+annotations_creators:
+- expert-generated
+language_creators:
+- expert-generated
+languages:
+- en
+licenses:
+- unknown
+multilinguality:
+- monolingual
+size_categories:
+- 1K<n<10K
+source_datasets:
+- original
+task_categories:
+- structure-prediction
+task_ids:
+- named-entity-recognition
+---
+
+# Dataset Card for [Dataset Name]
+
+## Table of Contents
+- [Dataset Card for [Dataset Name]](#dataset-card-for-dataset-name)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+  - [Dataset Structure](#dataset-structure)
+    - [Data Instances](#data-instances)
+    - [Data Fields](#data-fields)
+    - [Data Splits](#data-splits)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+    - [Annotations](#annotations)
+      - [Annotation process](#annotation-process)
+      - [Who are the annotators?](#who-are-the-annotators)
+    - [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:** [SPECIES](https://species.jensenlab.org/)
+- **Repository:**
+- **Paper:**
+- **Leaderboard:**
+- **Point of Contact:**
+
+### Dataset Summary
+
+[More Information Needed]
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+[More Information Needed]
+
+## Dataset Structure
+
+### Data Instances
+
+[More Information Needed]
+
+### Data Fields
+
+- `id`: Sentence identifier.  
+- `tokens`: Array of tokens composing a sentence.  
+- `ner_tags`: Array of tags, where `0` indicates no species mentioned, `1` signals the first token of a species and `2` the subsequent tokens of the species.  
+
+### Data Splits
+
+[More Information Needed]
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+[More Information Needed]
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed]
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+[More Information Needed]
+
+### Citation Information
+
+[More Information Needed]

dataset_infos.json

@@ -0,0 +1 @@
+{"species_800": {"description": "We have developed an efficient algorithm and implementation of a dictionary-based approach to named entity recognition,\nwhich we here use to identifynames of species and other taxa in text. The tool, SPECIES, is more than an order of\nmagnitude faster and as accurate as existing tools. The precision and recall was assessed both on an existing gold-standard\ncorpus and on a new corpus of 800 abstracts, which were manually annotated after the development of the tool. The corpus\ncomprises abstracts from journals selected to represent many taxonomic groups, which gives insights into which types of\norganism names are hard to detect and which are easy. Finally, we have tagged organism names in the entire Medline database\nand developed a web resource, ORGANISMS, that makes the results accessible to the broad community of biologists.\n", "citation": "@article{pafilis2013species,\n         title={The SPECIES and ORGANISMS resources for fast and accurate identification of taxonomic names in text},\n         author={Pafilis, Evangelos and Frankild, Sune P and Fanini, Lucia and Faulwetter, Sarah and Pavloudi, Christina and Vasileiadou, Aikaterini and Arvanitidis, Christos and Jensen, Lars Juhl},\n         journal={PloS one},\n         volume={8},\n         number={6},\n         pages={e65390},\n         year={2013},\n         publisher={Public Library of Science}\n}\n", "homepage": "https://species.jensenlab.org/", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "tokens": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner_tags": {"feature": {"num_classes": 3, "names": ["O", "B", "I"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "species800", "config_name": "species_800", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2579096, "num_examples": 5734, "dataset_name": "species800"}, "validation": {"name": "validation", "num_bytes": 385756, "num_examples": 831, "dataset_name": "species800"}, "test": {"name": "test", "num_bytes": 737760, "num_examples": 1631, "dataset_name": "species800"}}, "download_checksums": {"https://drive.google.com/u/0/uc?id=1OletxmPYNkz2ltOr9pyT0b0iBtUWxslh&export=download/": {"num_bytes": 18204624, "checksum": "30522c752fd90e6da05f117a52da13174b246e4980e46840e6e1737dc67e1d27"}}, "download_size": 18204624, "post_processing_size": null, "dataset_size": 3702612, "size_in_bytes": 21907236}}

dummy/species_800/1.0.0/dummy_data.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e2cfa3049113949db8de49f4de3160195b23cb1671d6499d54b9d7bc6272c4c4
+size 12082

species_800.py

@@ -0,0 +1,144 @@
+# coding=utf-8
+# Copyright 2020 HuggingFace Datasets Authors.
+#
+# 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
+"""The SPECIES and ORGANISMS Resources for Fast and Accurate Identification of Taxonomic Names in Text"""
+
+import logging
+import os
+
+import datasets
+
+
+_CITATION = """\
+@article{pafilis2013species,
+         title={The SPECIES and ORGANISMS resources for fast and accurate identification of taxonomic names in text},
+         author={Pafilis, Evangelos and Frankild, Sune P and Fanini, Lucia and Faulwetter, Sarah and Pavloudi, Christina and Vasileiadou, Aikaterini and Arvanitidis, Christos and Jensen, Lars Juhl},
+         journal={PloS one},
+         volume={8},
+         number={6},
+         pages={e65390},
+         year={2013},
+         publisher={Public Library of Science}
+}
+"""
+
+_DESCRIPTION = """\
+We have developed an efficient algorithm and implementation of a dictionary-based approach to named entity recognition,
+which we here use to identifynames of species and other taxa in text. The tool, SPECIES, is more than an order of
+magnitude faster and as accurate as existing tools. The precision and recall was assessed both on an existing gold-standard
+corpus and on a new corpus of 800 abstracts, which were manually annotated after the development of the tool. The corpus
+comprises abstracts from journals selected to represent many taxonomic groups, which gives insights into which types of
+organism names are hard to detect and which are easy. Finally, we have tagged organism names in the entire Medline database
+and developed a web resource, ORGANISMS, that makes the results accessible to the broad community of biologists.
+"""
+
+_HOMEPAGE = "https://species.jensenlab.org/"
+_URL = "https://drive.google.com/u/0/uc?id=1OletxmPYNkz2ltOr9pyT0b0iBtUWxslh&export=download/"
+_BIOBERT_NER_DATASET_DIRECTORY = "s800"
+_TRAINING_FILE = "train.tsv"
+_DEV_FILE = "devel.tsv"
+_TEST_FILE = "test.tsv"
+
+
+class Species800Config(datasets.BuilderConfig):
+    """BuilderConfig for Species800"""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig for Species800.
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(Species800Config, self).__init__(**kwargs)
+
+
+class Species800(datasets.GeneratorBasedBuilder):
+    """Species800 dataset."""
+
+    BUILDER_CONFIGS = [
+        Species800Config(name="species_800", version=datasets.Version("1.0.0"), description="Species800 dataset"),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "tokens": datasets.Sequence(datasets.Value("string")),
+                    "ner_tags": datasets.Sequence(
+                        datasets.features.ClassLabel(
+                            names=[
+                                "O",
+                                "B",
+                                "I",
+                            ]
+                        )
+                    ),
+                }
+            ),
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        urls_to_download = {
+            "biobert_ner_datasets": _URL,
+        }
+        downloaded_files = dl_manager.download_and_extract(urls_to_download)
+        dataset_directory = os.path.join(downloaded_files["biobert_ner_datasets"], _BIOBERT_NER_DATASET_DIRECTORY)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN, gen_kwargs={"filepath": os.path.join(dataset_directory, _TRAINING_FILE)}
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION, gen_kwargs={"filepath": os.path.join(dataset_directory, _DEV_FILE)}
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST, gen_kwargs={"filepath": os.path.join(dataset_directory, _TEST_FILE)}
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        logging.info("⏳ Generating examples from = %s", filepath)
+        with open(filepath, encoding="utf-8") as f:
+            guid = 0
+            tokens = []
+            ner_tags = []
+            for line in f:
+                if line.startswith("-DOCSTART-") or line == "" or line == "\n":
+                    if tokens:
+                        yield guid, {
+                            "id": str(guid),
+                            "tokens": tokens,
+                            "ner_tags": ner_tags,
+                        }
+                        guid += 1
+                        tokens = []
+                        ner_tags = []
+                else:
+                    # tokens are tab separated
+                    splits = line.split("\t")
+                    tokens.append(splits[0])
+                    ner_tags.append(splits[1].rstrip())
+            # last example
+            yield guid, {
+                "id": str(guid),
+                "tokens": tokens,
+                "ner_tags": ner_tags,
+            }