Fix missing tags in dataset cards (#4908)

Commit from https://github.com/huggingface/datasets/commit/c79e737b5247a908f6f63e4bcf9c62abd38ef6ee

README.md

@@ -16,10 +16,11 @@ size_categories:
 source_datasets:
 - original
 task_categories:
+- text2text-generation
 - text-generation
 - fill-mask
-- text-generation
-- fill-mask
+task_ids:
+- text2text-generation-other-code-generation
 - text-generation-other-code-modeling
 paperswithcode_id: null
 ---
@@ -52,16 +53,16 @@ paperswithcode_id: null
 ## Dataset Description
 
 - **homepage**: [py150](https://www.sri.inf.ethz.ch/py150) 
-- **Paper**: [Probabilistic Model for Code with Decision Trees](https://dl.acm.org/doi/10.1145/3022671.2984041)
+- **Paper**: [Probabilistic Model for Code with Decision Trees](https://www.semanticscholar.org/paper/Probabilistic-model-for-code-with-decision-trees-Raychev-Bielik/62e176977d439aac2e2d7eca834a7a99016dfcaf)
 - **Leaderboard:**
 - **Point of Contact:**
 
 ### Dataset Summary
 
-The dataset consists of parsed Parsed ASTs that were used to train and evaluate the DeepSyn tool. 
+The dataset consists of parsed ASTs that were used to train and evaluate the DeepSyn tool.
 The Python programs are collected from GitHub repositories
-by removing duplicate files, removing project forks (copy of another existing repository)
-,keeping only programs that parse and have at most 30'000 nodes in the AST and 
+by removing duplicate files, removing project forks (copy of another existing repository),
+keeping only programs that parse and have at most 30'000 nodes in the AST and
 we aim to remove obfuscated files
 
 ### Supported Tasks and Leaderboards
@@ -155,6 +156,25 @@ authors={Raychev, V., Bielik, P., and Vechev, M.},
 year={2016}
 }
 
+```
+@inproceedings{10.1145/2983990.2984041,
+author = {Raychev, Veselin and Bielik, Pavol and Vechev, Martin},
+title = {Probabilistic Model for Code with Decision Trees},
+year = {2016},
+isbn = {9781450344449},
+publisher = {Association for Computing Machinery},
+address = {New York, NY, USA},
+url = {https://doi.org/10.1145/2983990.2984041},
+doi = {10.1145/2983990.2984041},
+booktitle = {Proceedings of the 2016 ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applications},
+pages = {731–747},
+numpages = {17},
+keywords = {Code Completion, Decision Trees, Probabilistic Models of Code},
+location = {Amsterdam, Netherlands},
+series = {OOPSLA 2016}
+}
+```
+
 ### Contributions
 
 Thanks to [@reshinthadithyan](https://github.com/reshinthadithyan) for adding this dataset.

dataset_infos.json

@@ -1 +1 @@
-{"ast": {"description": "dataset consisting of parsed Parsed ASTs that were used to train and\nevaluate the DeepSyn tool.\nThe Python programs are collected from GitHub repositories\nby removing duplicate files, removing project forks (copy of another existing repository)\n,keeping only programs that parse and have at most 30'000 nodes in the AST and\nwe aim to remove obfuscated files", "citation": "@InProceedings{OOPSLA \u201916, ACM,\ntitle = {Probabilistic Model for Code with Decision Trees.},\nauthors={Raychev, V., Bielik, P., and Vechev, M.},\nyear={2016}\n}\n", "homepage": "https://www.sri.inf.ethz.ch/py150", "license": "", "features": {"ast": {"feature": {"type": {"dtype": "string", "id": null, "_type": "Value"}, "value": {"dtype": "string", "id": null, "_type": "Value"}, "children": {"feature": {"dtype": "int32", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": {"input": "ast", "output": ""}, "builder_name": "py_ast", "config_name": "ast", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1870790180, "num_examples": 100000, "dataset_name": "py_ast"}, "test": {"name": "test", "num_bytes": 907514993, "num_examples": 50000, "dataset_name": "py_ast"}}, "download_checksums": {"http://files.srl.inf.ethz.ch/data/py150.tar.gz": {"num_bytes": 526642289, "checksum": "4093b331d43c795e39fb5f156ccb7dcbb04c5d745d5e840c2d6926c11292dbd4"}}, "download_size": 526642289, "post_processing_size": null, "dataset_size": 2778305173, "size_in_bytes": 3304947462}}
+{"ast": {"description": "Dataset consisting of parsed ASTs that were used to train and\nevaluate the DeepSyn tool.\nThe Python programs are collected from GitHub repositories\nby removing duplicate files, removing project forks (copy of another existing repository)\n,keeping only programs that parse and have at most 30'000 nodes in the AST and\nwe aim to remove obfuscated files", "citation": "@InProceedings{OOPSLA \u201916, ACM,\ntitle = {Probabilistic Model for Code with Decision Trees.},\nauthors={Raychev, V., Bielik, P., and Vechev, M.},\nyear={2016}\n}\n", "homepage": "https://www.sri.inf.ethz.ch/py150", "license": "", "features": {"ast": {"feature": {"type": {"dtype": "string", "id": null, "_type": "Value"}, "value": {"dtype": "string", "id": null, "_type": "Value"}, "children": {"feature": {"dtype": "int32", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": {"input": "ast", "output": ""}, "builder_name": "py_ast", "config_name": "ast", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1870790180, "num_examples": 100000, "dataset_name": "py_ast"}, "test": {"name": "test", "num_bytes": 907514993, "num_examples": 50000, "dataset_name": "py_ast"}}, "download_checksums": {"http://files.srl.inf.ethz.ch/data/py150.tar.gz": {"num_bytes": 526642289, "checksum": "4093b331d43c795e39fb5f156ccb7dcbb04c5d745d5e840c2d6926c11292dbd4"}}, "download_size": 526642289, "post_processing_size": null, "dataset_size": 2778305173, "size_in_bytes": 3304947462}}

py_ast.py

@@ -33,7 +33,7 @@ year={2016}
 # TODO: Add description of the dataset here
 # You can copy an official description
 _DESCRIPTION = """\
-dataset consisting of parsed Parsed ASTs that were used to train and
+Dataset consisting of parsed ASTs that were used to train and
 evaluate the DeepSyn tool.
 The Python programs are collected from GitHub repositories
 by removing duplicate files, removing project forks (copy of another existing repository)