Trim verbose UI intro

app.py

@@ -966,26 +966,9 @@ with gr.Blocks(title="LWM-Spectro Lab") as demo:
     gr.Markdown(f"**{DATASET_STATUS}**")
     gr.Markdown(
         """
-**Having trouble seeing plots/images?**
-
-- This Space is currently **private**. If you're not logged into an account with access, the embedded app may appear blank.
-- Some browsers block authentication cookies inside the Hugging Face embed iframe.
-  If you see empty galleries/plots on `huggingface.co/spaces`, open the direct app URL instead:
-  **https://wi-lab-lwm-spectro.hf.space**
+Interactive lab for exploring LWM spectrogram embeddings and cached MoE probes.
 """
     )
-    gr.Markdown(
-        """
-    Interactive lab for exploring **LWM spectrogram embeddings** on Sub-6 GHz I/Q baseband data.
-    Browse the bundled DeepMIMO-derived samples (LTE / WiFi / 5G, 128×128 spectrograms, 10.5k total),
-    compare LWM embeddings against raw spectrogram vectors, and probe precomputed MoE embeddings for joint SNR/mobility.
-
-    **What you get**
-    - **Data slices:** LTE / WiFi / 5G Sub-6 GHz I/Q baseband spectrograms with modulation, SNR, and mobility labels; 500 samples per SNR per tech (7 SNRs).
-    - **Visualization:** Peek at the raw 128×128 Sub-6 GHz I/Q baseband spectrograms, and compare LWM tech-specific embeddings vs. normalized raw vectors via balanced t-SNE.
-    - **Lightweight probes:** Run k-NN prototypes for per-tech modulation recognition and joint SNR/Doppler classification using the cached MoE embeddings alongside raw baselines.
-    """
-    )
 
     with gr.Tabs():
         with gr.Tab("Spectrograms"):