Adding Huggingface modelhub dataset

.gitattributes

@@ -14,3 +14,4 @@
 *.pb filter=lfs diff=lfs merge=lfs -text
 *.pt filter=lfs diff=lfs merge=lfs -text
 *.pth filter=lfs diff=lfs merge=lfs -text
+huggingface-modelhub.csv filter=lfs diff=lfs merge=lfs -text

dataset_infos.json

@@ -0,0 +1 @@
+{"default": {"description": "Metadata of the information available on HuggingFace's modelhub\n", "citation": "\n", "homepage": "https://huggingface.co/models", "license": "", "features": {"modelId": {"dtype": "string", "id": null, "_type": "Value"}, "lastModified": {"dtype": "string", "id": null, "_type": "Value"}, "tags": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "pipeline_tag": {"dtype": "string", "id": null, "_type": "Value"}, "files": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "publishedBy": {"dtype": "string", "id": null, "_type": "Value"}, "modelCard": {"dtype": "large_string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "hate_speech_offensive", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 21457237, "num_examples": 10354, "dataset_name": "hate_speech_offensive"}}, "download_checksums": {"huggingface-modelhub.csv": {"num_bytes": 21341037, "checksum": "53d63e7c4fab45592c34bf52927e397377be731cfed82568718bcba27523d85c"}}, "download_size": 21341037, "post_processing_size": null, "dataset_size": 21457237, "size_in_bytes": 42798274}}

huggingface-modelhub.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:53d63e7c4fab45592c34bf52927e397377be731cfed82568718bcba27523d85c
+size 21341037

huggingface-modelhub.py

@@ -0,0 +1,95 @@
+# coding=utf-8
+# 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.
+"""Metadata of the information available on HuggingFace's modelhub."""
+
+
+import ast
+import csv
+
+import datasets
+# Some readme files on modelhub are large in size
+csv.field_size_limit(100000000)
+
+_CITATION = """\
+
+"""
+
+_DESCRIPTION = """\
+Metadata of the information available on HuggingFace's modelhub
+"""
+
+_HOMEPAGE = "https://huggingface.co/models"
+
+_LICENSE = ""
+
+_URL = "huggingface-modelhub.csv"
+
+
+
+class HuggingfaceModelhub(datasets.GeneratorBasedBuilder):
+    """Metadata of the information available on HuggingFace's modelhub"""
+
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "modelId": datasets.Value("string"),
+                    "lastModified": datasets.Value("string"),
+                    "tags": datasets.features.Sequence(datasets.Value("string")),
+                    "pipeline_tag": datasets.Value("string"),
+                    "files": datasets.features.Sequence(datasets.Value("string")),
+                    "publishedBy": datasets.Value("string"),
+                    "modelCard": datasets.Value("large_string"),
+                }
+            ),
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+
+        data_file = dl_manager.download_and_extract(_URL)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": data_file,
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        """Yields examples."""
+
+        with open(filepath, encoding="utf-8") as f:
+            reader = csv.reader(f)
+            for id_, row in enumerate(reader):
+                if id_ == 0:
+                    continue
+
+                yield id_, {
+                    "modelId": row[0],
+                    "lastModified": row[1],
+                    "tags": ast.literal_eval(row[2]),
+                    "pipeline_tag": row[3],
+                    "files": ast.literal_eval(row[4]),
+                    "publishedBy": row[5],
+                    "modelCard": row[6]
+                }