deploy via scripts/deploy_to_space.py

README.md

@@ -1,5 +1,5 @@
 ---
-title: Qubit-Medic
+title: QuantumScribe
 emoji: 🩺
 colorFrom: indigo
 colorTo: pink
@@ -19,7 +19,7 @@ license: mit
 short_description: OpenEnv RL env that teaches an LLM to decode quantum errors.
 ---
 
-# Qubit-Medic: An LLM Decoder for Quantum Error Correction
+# QuantumScribe: An LLM Decoder for Quantum Error Correction
 
 An LLM (Qwen2.5-3B-Instruct) learning to outperform a 50-year-old graph-matching algorithm (PyMatching) at decoding quantum surface-code syndromes — using verifiable physics rewards, not human preferences. DeepMind's AlphaQubit (*Nature* 2024, Bausch et al.) showed a transformer can beat strong classical decoders, but it cost Google millions of dollars and a custom architecture. We ship a 3B-parameter open model on a free Colab T4, trained with SFT + GRPO against a real Stim simulator behind an OpenEnv HTTP contract.
 
@@ -31,10 +31,10 @@ An LLM (Qwen2.5-3B-Instruct) learning to outperform a 50-year-old graph-matching
 - **Trained LoRA on the Hub:** [ronitraj/quantumscribe](https://huggingface.co/ronitraj/quantumscribe)
 - **Colab notebook (actual training run):** [`notebooks/meta_final.ipynb`](notebooks/meta_final.ipynb)
 - **2-min video:** <!-- TODO: replace with submission video URL -->TBD-replace
-- **Blog:** <!-- TODO: replace with blog post URL -->TBD-replace
+- **Blog:** [`BLOG.md`](BLOG.md)
 - **W&B project:** [ronitraj/QuantumScribe-GRPO](https://wandb.ai/ronitraj/QuantumScribe-GRPO) · SFT [`yli513jl`](https://wandb.ai/ronitraj/QuantumScribe-GRPO/runs/yli513jl) · GRPO [`4p7eurnc`](https://wandb.ai/ronitraj/QuantumScribe-GRPO/runs/4p7eurnc)
 - **OpenEnv manifest:** [`openenv.yaml`](openenv.yaml)
-- **Mini-blog (judges' walkthrough):** [`BLOG.md`](BLOG.md)
+
 
 ---