Add README

README.md

@@ -1,19 +1,47 @@
 ---
-dataset_info:
-  features:
-  - name: seed
-    dtype: string
-  - name: source
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 150513715
-    num_examples: 314318
-  download_size: 72521120
-  dataset_size: 150513715
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+language:
+- en
+license: other
+tags:
+- code
+- seeds
+- oss-instruct
+- dataset-curation
 ---
+
+# oss-code-seeds
+
+A combined dataset of open-source code snippets (seeds) curated from multiple
+high-quality sources. The intended use is to serve as seeds for generating
+coding instruction-response pairs via the OSS-Instruct approach — where a model
+is prompted with a real code snippet to produce a grounded, diverse coding problem
+and its solution.
+
+## Columns
+
+- `seed`: A raw code snippet from open-source software (OSS), serving as the seed
+- `source`: The original HuggingFace dataset the seed was taken from
+
+## Sources
+
+| Dataset | Description |
+|---|---|
+| `ise-uiuc/Magicoder-OSS-Instruct-75K` | Seeds used to generate the Magicoder dataset via GPT-3.5, multi-language GitHub snippets |
+| `bigcode/self-oss-instruct-sc2-concepts` | Filtered Python functions from The Stack V1 used in the SelfCodeAlign pipeline |
+
+## Intended Use
+
+Feed the `seed` column into your own model API to generate coding problems and
+solutions, effectively replicating or improving upon the OSS-Instruct pipeline
+with your own model.
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("PursuitOfDataScience/oss-code-seeds", split="train")
+
+for row in ds:
+    seed = row["seed"]
+    source = row["source"]
+    # prompt your model with seed to generate a problem + solution
+```