Datasets:
Tasks:
Text Classification
Modalities:
Text
Sub-tasks:
sentiment-classification
Languages:
Indonesian
Size:
10K - 100K
License:
andreaschandra
commited on
Commit
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4030949
1
Parent(s):
bed3db5
update path
Browse files- dataset_infos.json +1 -1
- google-play-review.py +2 -2
dataset_infos.json
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{"default": {"description": "This dataset is built as a playground for beginner to make a use case for creating sentiment analysis model.\n", "citation": "", "homepage": "https://github.com/jakartaresearch", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "stars": {"dtype": "int8", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "google_play_review", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 480786, "num_examples": 7028, "dataset_name": "google_play_review"}, "validation": {"name": "validation", "num_bytes": 216876, "num_examples": 3012, "dataset_name": "google_play_review"}}, "download_checksums": {"https://
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{"default": {"description": "This dataset is built as a playground for beginner to make a use case for creating sentiment analysis model.\n", "citation": "", "homepage": "https://github.com/jakartaresearch", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "stars": {"dtype": "int8", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "google_play_review", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 480786, "num_examples": 7028, "dataset_name": "google_play_review"}, "validation": {"name": "validation", "num_bytes": 216876, "num_examples": 3012, "dataset_name": "google_play_review"}}, "download_checksums": {"https://media.githubusercontent.com/media/jakartaresearch/hf-datasets/main/google-play-review/google-play-review/train.csv": {"num_bytes": 455952, "checksum": "640c1096168259bea951919369011827aeee0b873d386dd62d5c52c62c9c34f5"}, "https://media.githubusercontent.com/media/jakartaresearch/hf-datasets/main/google-play-review/google-play-review/validation.csv": {"num_bytes": 206369, "checksum": "a6f7a94d76dc2375496e64b3cd1fc0e6d857c137984bcf8de321446d8d482a68"}}, "download_size": 662321, "post_processing_size": null, "dataset_size": 697662, "size_in_bytes": 1359983}}
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google-play-review.py
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# TODO: Add link to the official dataset URLs here
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# The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
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# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
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_TRAIN_URL = "https://
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_VAL_URL = "https://
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# TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case
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# TODO: Add link to the official dataset URLs here
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# The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
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# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
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_TRAIN_URL = "https://media.githubusercontent.com/media/jakartaresearch/hf-datasets/main/google-play-review/google-play-review/train.csv"
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_VAL_URL = "https://media.githubusercontent.com/media/jakartaresearch/hf-datasets/main/google-play-review/google-play-review/validation.csv"
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# TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case
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