Update README.md

README.md

@@ -1,3 +1,57 @@
----
-license: cc
----
+---
+license: cc
+language:
+- en
+tags:
+- medical
+- spelling
+- counting
+- qa
+- grpo
+task_categories:
+- question-answering
+pretty_name: MedSpellCount-QA
+---
+
+# MedSpellCount-QA
+
+## Dataset Summary
+**MedSpellCount-QA** is a lightweight dataset for **orthographic counting** framed as question-answering over medical terms.  
+Each `input` is a short natural-language question like:
+
+> *“How many **r** are in **warfarine**?”*
+
+The `output` is the **correct count** as an integer (e.g., `1`). This format is convenient for **GRPO** (Group Relative Policy Optimization) or other RL-style post-training, where a simple correctness reward compares multiple candidates per prompt.
+
+*Why a distinct dataset?* Counting letters in real medical vocabulary is a simple, objective task that stresses **spelling attention** and **string reasoning** without requiring external knowledge.
+
+## Use Cases
+- **GRPO training**: generate K candidates per prompt and reward exact correctness.  
+- **Instruction/QA fine-tuning** for robustness to orthographic queries.  
+- **Eval** of character-level attention and tokenization effects on medical terms.
+
+## Languages
+- **English** prompts; terms are predominantly **medical**.
+
+## Dataset Structure
+
+### Data Fields
+- **input** *(string, required)*: the question, e.g.,  
+  `How many 'r' in 'warfarine'?`
+- **output** *(integer, required)*: the correct count as text, e.g., `1`.
+
+### Data Instances
+```json
+{
+  "input": "How many 'r' in 'warfarine'?",
+  "output": 1
+}
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("mkurmanmkurman/MedSpellCount-QA", split='train')  # or mkurman/medspellcount-qa if you rename
+
+print(ds)
+print(ds[0])
+```