Update README.md

README.md

@@ -1,3 +1,143 @@
 ---
+annotations_creators: 
+- crowdsourced
 license: other
+language_creators:
+- crowdsourced
+language:
+- code
+task_categories:
+- text-generation
+tags:
+- code, kotlin, native Android development, curated, training
+size_categories:
+- 100K<n<1M
+source_datasets: []
+pretty_name: iva-kotlin-codeint-clean
+task_ids:
+- language-modeling
 ---
+
+# IVA Kotlin GitHub Code Dataset
+
+## Dataset Description
+
+This is the curated train split of IVA Kotlin dataset extracted from GitHub. 
+It contains curated Kotlin files gathered with the purpose to train a code generation model.
+
+The dataset consists of 383380 Kotlin code files from GitHub.
+[Here is the unsliced curated dataset](https://huggingface.co/datasets/mvasiliniuc/iva-kotlin-codeint-clean) and [here is the raw dataset](https://huggingface.co/datasets/mvasiliniuc/iva-kotlin-codeint).
+
+### How to use it
+
+To download the full dataset:
+
+```python
+from datasets import load_dataset
+dataset = load_dataset('mvasiliniuc/iva-kotlin-codeint-clean-train', split='train'))
+```
+
+
+## Data Structure
+
+### Data Fields
+
+|Field|Type|Description|
+|---|---|---|
+|repo_name|string|name of the GitHub repository|
+|path|string|path of the file in GitHub repository|
+|copies|string|number of occurrences in dataset|
+|content|string|content of source file|
+|size|string|size of the source file in bytes|
+|license|string|license of GitHub repository|
+|hash|string|Hash of content field.|
+|line_mean|number|Mean line length of the content.
+|line_max|number|Max line length of the content.
+|alpha_frac|number|Fraction between mean and max line length of content.
+|ratio|number|Character/token ratio of the file with tokenizer.
+|autogenerated|boolean|True if the content is autogenerated by looking for keywords in the first few lines of the file.
+|config_or_test|boolean|True if the content is a configuration file or a unit test.
+|has_no_keywords|boolean|True if a file has none of the keywords for Kotlin Programming Language.
+|has_few_assignments|boolean|True if file uses symbol '=' less than `minimum` times.
+
+### Instance
+
+```json
+{
+   "repo_name":"oboenikui/UnivCoopFeliCaReader",
+   "path":"app/src/main/java/com/oboenikui/campusfelica/ScannerActivity.kt",
+   "copies":"1",
+   "size":"5635",
+   "content":"....",
+   "license":"apache-2.0",
+   "hash":"e88cfd99346cbef640fc540aac3bf20b",
+   "line_mean":37.8620689655,
+   "line_max":199,
+   "alpha_frac":0.5724933452,
+   "ratio":5.0222816399,
+   "autogenerated":false,
+   "config_or_test":false,
+   "has_no_keywords":false,
+   "has_few_assignments":false
+}
+```
+
+## Languages
+
+The dataset contains only Kotlin files.
+
+```json
+{
+    "Kotlin": [".kt"]
+}
+```
+
+## Licenses
+
+Each entry in the dataset contains the associated license. The following is a list of licenses involved and their occurrences.
+
+```json
+{
+   "agpl-3.0":3209,
+   "apache-2.0":90782,
+   "artistic-2.0":130,
+   "bsd-2-clause":380,
+   "bsd-3-clause":3584,
+   "cc0-1.0":155,
+   "epl-1.0":792,
+   "gpl-2.0":4432,
+   "gpl-3.0":19816,
+   "isc":345,
+   "lgpl-2.1":118,
+   "lgpl-3.0":2689,
+   "mit":31470,
+   "mpl-2.0":1444,
+   "unlicense":654
+}
+```
+
+## Dataset Statistics
+
+```json
+{
+    "Total size": "~207 MB",
+    "Number of files": 160000,
+    "Number of files under 500 bytes": 2957,
+    "Average file size in bytes": 5199,
+}
+```
+
+## Curation Process
+
+See [the unsliced curated dataset](https://huggingface.co/datasets/mvasiliniuc/iva-kotlin-codeint-clean) for mode details.
+
+## Data Splits
+
+The dataset only contains a train split focused only on training data. For validation and unspliced versions, please check the following links:
+* Clean Version Unsliced: https://huggingface.co/datasets/mvasiliniuc/iva-kotlin-codeint-clean
+* Clean Version Valid: https://huggingface.co/datasets/mvasiliniuc/iva-kotlin-codeint-clean-valid
+
+# Considerations for Using the Data
+
+The dataset consists of source code from a wide range of repositories. 
+As such they can potentially include harmful or biased code as well as sensitive information like passwords or usernames.