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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
-*.bz2 filter=lfs diff=lfs merge=lfs -text
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-*.parquet filter=lfs diff=lfs merge=lfs -text
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-*.pickle filter=lfs diff=lfs merge=lfs -text
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-*.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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-*tfevents* filter=lfs diff=lfs merge=lfs -text
-# Audio files - uncompressed
-*.pcm filter=lfs diff=lfs merge=lfs -text
-*.sam filter=lfs diff=lfs merge=lfs -text
-*.raw filter=lfs diff=lfs merge=lfs -text
-# Audio files - compressed
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README.md

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----
-annotations_creators:
-- expert-generated
-language:
-- en
-language_creators:
-- found
-license:
-- other
-multilinguality:
-- monolingual
-paperswithcode_id: conll-2003
-pretty_name: FavsBot
-size_categories:
-- 10K<n<100K
-source_datasets:
-- extended|other-reuters-corpus
-tags:
-- Bot
-task_categories:
-- token-classification
-task_ids:
-- named-entity-recognition
-train-eval-index:
-- col_mapping:
-    ner_tags: tags
-    tokens: tokens
-  metrics:
-  - name: seqeval
-    type: seqeval
-  splits:
-    eval_split: test
-    train_split: train
-  task: token-classification
-  task_id: entity_extraction
----

default/favs_bot-test.parquet

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default/favs_bot-train.parquet

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default/favs_bot-validation.parquet

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favs_bot.py

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-# Inspired by conll2003 dataset
-# https://huggingface.co/datasets/conll2003
-
-
-# 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
-"""Introduction to the CoNLL-2003 Shared Task: Language-Independent Named Entity Recognition"""
-
-import os
-
-import datasets
-
-
-logger = datasets.logging.get_logger(__name__)
-
-
-_CITATION = """\
-@inproceedings{tjong-kim-sang-de-meulder-2003-introduction,
-  title = "Introduction to the {C}o{NLL}-2003 Shared Task: Language-Independent Named Entity Recognition",
-  author = "Tjong Kim Sang, Erik F.  and
-    De Meulder, Fien",
-  booktitle = "Proceedings of the Seventh Conference on Natural Language Learning at {HLT}-{NAACL} 2003",
-  year = "2003",
-  url = "https://www.aclweb.org/anthology/W03-0419",
-  pages = "142--147",
-}
-"""
-
-_DESCRIPTION = """\
-The shared task of CoNLL-2003 concerns language-independent named entity recognition. We will concentrate on
-four types of named entities: persons, locations, organizations and names of miscellaneous entities that do
-not belong to the previous three groups.
-
-The CoNLL-2003 shared task data files contain four columns separated by a single space. Each word has been put on
-a separate line and there is an empty line after each sentence. The first item on each line is a word, the second
-a part-of-speech (POS) tag, the third a syntactic chunk tag and the fourth the named entity tag. The chunk tags
-and the named entity tags have the format I-TYPE which means that the word is inside a phrase of type TYPE. Only
-if two phrases of the same type immediately follow each other, the first word of the second phrase will have tag
-B-TYPE to show that it starts a new phrase. A word with tag O is not part of a phrase. Note the dataset uses IOB2
-tagging scheme, whereas the original dataset uses IOB1.
-
-For more details see https://www.clips.uantwerpen.be/conll2003/ner/ and https://www.aclweb.org/anthology/W03-0419
-"""
-
-_URL = "https://data.deepai.org/conll2003.zip"
-_TRAINING_FILE = "train.txt"
-_DEV_FILE = "valid.txt"
-_TEST_FILE = "test.txt"
-
-
-# class Conll2003Config(datasets.BuilderConfig):
-#     """BuilderConfig for Conll2003"""
-
-#     def __init__(self, **kwargs):
-#         """BuilderConfig forConll2003.
-
-#         Args:
-#           **kwargs: keyword arguments forwarded to super.
-#         """
-#         super(Conll2003Config, self).__init__(**kwargs)
-
-
-class Conll2003(datasets.GeneratorBasedBuilder):
-    # """Conll2003 dataset."""
-
-    # BUILDER_CONFIGS = [
-    #     Conll2003Config(name="conll2003", version=datasets.Version(
-    #         "1.0.0"), description="Conll2003 dataset"),
-    # ]
-
-    VERSION = datasets.Version("1.1.0")
-    DEFAULT_CONFIG_NAME = "first_domain"
-    BUILDER_CONFIGS = [
-        # datasets.BuilderConfig(name="first_domain", version=VERSION,
-        #                        description="This part of my dataset covers a first domain"),
-        # datasets.BuilderConfig(name="second_domain", version=VERSION,
-        #                        description="This part of my dataset covers a second domain"),
-    ]
-
-    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-PER",
-                                "I-PER",
-                                "B-TAG",
-                                "I-TAG",
-                                "B-LOC",
-                                "I-LOC",
-                                "B-TIME",
-                                "I-TIME",
-                                "B-SORT",
-                                "I-SORT"
-                            ]
-                        )
-                    ),
-                }
-            ),
-            supervised_keys=None,
-            homepage="https://www.aclweb.org/anthology/W03-0419/",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        # downloaded_file = dl_manager.download_and_extract(_URL)
-        # data_files = {
-        #     "train": os.path.join(downloaded_file, _TRAINING_FILE),
-        #     "dev": os.path.join(downloaded_file, _DEV_FILE),
-        #     "test": os.path.join(downloaded_file, _TEST_FILE),
-        # }
-
-        # data_files = {
-        #     "train": os.path.join(downloaded_file, _TRAINING_FILE),
-        #     "dev": os.path.join(downloaded_file, _DEV_FILE),
-        #     "test": os.path.join(downloaded_file, _TEST_FILE),
-        # }
-
-        url = "https://pastebin.pl/view/raw/f1bffd94"
-        text_file = dl_manager.download(url)
-
-        data_files = {
-            "train": text_file,
-            "dev": text_file,
-            "test": text_file,
-        }
-
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={
-                                    "filepath": data_files["train"]}),
-            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={
-                                    "filepath": data_files["dev"]}),
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={
-                                    "filepath": data_files["test"]}),
-        ]
-
-    def _generate_examples(self, filepath):
-        logger.info("⏳ Generating examples from = %s", filepath)
-        with open(filepath, encoding="utf-8") as f:
-            guid = 0
-            tokens = []
-            pos_tags = []
-            chunk_tags = []
-            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:
-                    # conll2003 tokens are space separated
-                    splits = line.split(" ")
-                    tokens.append(splits[0])
-                    ner_tags.append(splits[1].rstrip())
-            # last example
-            if tokens:
-                yield guid, {
-                    "id": str(guid),
-                    "tokens": tokens,
-                    "ner_tags": ner_tags,
-                }