doc: usage guide addition

README.md

@@ -28,6 +28,9 @@ This dataset is a remastered version prepared using [Adaption's](https://adaptio
 
 This dataset contains pairs of abstract OpenQASM 2.0 quantum circuits and their hardware-compliant compiled versions. Each sample specifies a target qubit topology (e.g., Star, Ring, Linear, Grid, HeavyHex) and coupling map constraints. The compiled outputs include necessary SWAP gates inserted to satisfy physical connectivity requirements while minimizing circuit depth.
 
+> **Dataset Motto:**  
+> *"Embedding physical spatial graph calculus into LLM weight space to eliminate graph hallucinations and enable deterministic quantum hardware circuit routing."*
+
 ### Dataset size
 
 There are 15,000 data points in this dataset. This is an instruction tuning dataset.
@@ -56,3 +59,50 @@ The final quality is B, with a relative quality improvement of -26.0%.
 
 - **Percentile Chart:**
 <img src="https://proteus-prod-public.s3.us-east-1.amazonaws.com/temp/52761e13-0dea-4c29-a368-9cbac7fec0fe.png" alt="Percentile Chart" style="max-width: 50%; display: block; margin-left: auto; margin-right: auto;" />
+
+---
+
+### Usage & Quickstart
+
+Load the dataset directly using the Hugging Face `datasets` library:
+
+```python
+from datasets import load_dataset
+
+# Load the instruction-tuning dataset
+dataset = load_dataset("jay2219/quantum-circuit-routing")
+
+# Inspect a sample training pair
+sample = dataset["train"][0]
+print("System Role:\n", sample["messages"][0]["content"])
+print("User Prompt (Abstract QASM & Topology):\n", sample["messages"][1]["content"])
+print("Assistant Response (Routed Compliant QASM):\n", sample["messages"][2]["content"])
+```
+
+---
+
+### Data Schema & Fields
+
+Each record follows the standard OpenAI Chat format:
+- **`messages[0]` (`system`)**: Enforces deterministic quantum hardware compilation role and strict OpenQASM output requirements.
+- **`messages[1]` (`user`)**: Specifies the physical hardware topology, qubit count, explicit coupling map (valid edge list), hardware constraints, and input abstract OpenQASM 2.0.
+- **`messages[2]` (`assistant`)**: Compiled OpenQASM 2.0 code containing minimal SWAP gate insertions to satisfy physical coupling map adjacency constraints.
+
+---
+
+### Hardware Topologies Covered
+
+The 15,000 instruction-tuning samples span 5 distinct physical quantum hardware architectures:
+1. **Linear:** 1D line chain topology (e.g. 5–15 qubits).
+2. **Ring:** 1D closed-loop ring topology.
+3. **Star:** Central hub routing graph (all peripheral qubits connect through hub node 0).
+4. **Grid:** 2D rectangular lattice QPU connectivity graphs (e.g. 2x2 up to 5x3).
+5. **HeavyHex:** IBM Heavy-Hex lattice architecture.
+
+---
+
+### Associated Models & Evaluation Benchmarks
+
+- **Fine-Tuned Model:** [`jay2219/Q-Route-70B`](https://huggingface.co/jay2219/Q-Route-70B)
+- **Held-Out Evaluation Benchmark:** [`jay2219/Q-Route-Benchmark`](https://huggingface.co/datasets/jay2219/Q-Route-Benchmark) (100 non-overlapping evaluation circuits with 0% data contamination)
+