Host data file (#3)

- Host data file (19bd22e0d72e279f4ca3882715147a39e4c56141)
- Update loading script (4a4ae421738810e3d5d9454a7fe05bba68ee50e3)
- Delete legacy dataset_infos.json (688c37adadd6876e21982b41c328b1054fccb1b1)

data/tifu_all_tokenized_and_filtered.json.gz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4eea57413cabfb2aeee24cd944f1ed9c84ccebb2cf062b307c2130d44159d8de
+size 141774816

dataset_infos.json

@@ -1 +0,0 @@
-{"short": {"description": "\nReddit dataset, where TIFU denotes the name of subbreddit /r/tifu.\nAs defined in the publication, styel \"short\" uses title as summary and\n\"long\" uses tldr as summary.\n\nFeatures includes:\n  - document: post text without tldr.\n  - tldr: tldr line.\n  - title: trimmed title without tldr.\n  - ups: upvotes.\n  - score: score.\n  - num_comments: number of comments.\n  - upvote_ratio: upvote ratio.\n", "citation": "\n@misc{kim2018abstractive,\n    title={Abstractive Summarization of Reddit Posts with Multi-level Memory Networks},\n    author={Byeongchang Kim and Hyunwoo Kim and Gunhee Kim},\n    year={2018},\n    eprint={1811.00783},\n    archivePrefix={arXiv},\n    primaryClass={cs.CL}\n}\n", "homepage": "https://github.com/ctr4si/MMN", "license": "", "features": {"ups": {"dtype": "float32", "id": null, "_type": "Value"}, "num_comments": {"dtype": "float32", "id": null, "_type": "Value"}, "upvote_ratio": {"dtype": "float32", "id": null, "_type": "Value"}, "score": {"dtype": "float32", "id": null, "_type": "Value"}, "documents": {"dtype": "string", "id": null, "_type": "Value"}, "tldr": {"dtype": "string", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": {"input": "documents", "output": "title"}, "task_templates": null, "builder_name": "reddit_tifu", "config_name": "short", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 137715925, "num_examples": 79740, "dataset_name": "reddit_tifu"}}, "download_checksums": {"https://drive.google.com/uc?export=download&confirm=t&id=1ffWfITKFMJeqjT8loC8aiCLRNJpc_XnF": {"num_bytes": 670607856, "checksum": "f175cafe348e0521c2424cd419c934d10c6af613ed8cbe8eaa8cfbaa06377f1a"}}, "download_size": 670607856, "post_processing_size": null, "dataset_size": 137715925, "size_in_bytes": 808323781}, "long": {"description": "\nReddit dataset, where TIFU denotes the name of subbreddit /r/tifu.\nAs defined in the publication, styel \"short\" uses title as summary and\n\"long\" uses tldr as summary.\n\nFeatures includes:\n  - document: post text without tldr.\n  - tldr: tldr line.\n  - title: trimmed title without tldr.\n  - ups: upvotes.\n  - score: score.\n  - num_comments: number of comments.\n  - upvote_ratio: upvote ratio.\n", "citation": "\n@misc{kim2018abstractive,\n    title={Abstractive Summarization of Reddit Posts with Multi-level Memory Networks},\n    author={Byeongchang Kim and Hyunwoo Kim and Gunhee Kim},\n    year={2018},\n    eprint={1811.00783},\n    archivePrefix={arXiv},\n    primaryClass={cs.CL}\n}\n", "homepage": "https://github.com/ctr4si/MMN", "license": "", "features": {"ups": {"dtype": "float32", "id": null, "_type": "Value"}, "num_comments": {"dtype": "float32", "id": null, "_type": "Value"}, "upvote_ratio": {"dtype": "float32", "id": null, "_type": "Value"}, "score": {"dtype": "float32", "id": null, "_type": "Value"}, "documents": {"dtype": "string", "id": null, "_type": "Value"}, "tldr": {"dtype": "string", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": {"input": "documents", "output": "tldr"}, "task_templates": null, "builder_name": "reddit_tifu", "config_name": "long", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 91984758, "num_examples": 42139, "dataset_name": "reddit_tifu"}}, "download_checksums": {"https://drive.google.com/uc?export=download&confirm=t&id=1ffWfITKFMJeqjT8loC8aiCLRNJpc_XnF": {"num_bytes": 670607856, "checksum": "f175cafe348e0521c2424cd419c934d10c6af613ed8cbe8eaa8cfbaa06377f1a"}}, "download_size": 670607856, "post_processing_size": null, "dataset_size": 91984758, "size_in_bytes": 762592614}}

reddit_tifu.py

@@ -48,7 +48,7 @@ Features includes:
   - upvote_ratio: upvote ratio.
 """
 
-_URL = "https://drive.google.com/uc?export=download&confirm=t&id=1ffWfITKFMJeqjT8loC8aiCLRNJpc_XnF"
+_URL = "data/tifu_all_tokenized_and_filtered.json.gz"
 
 _DOCUMENT = "documents"
 _TITLE = "title"