Add GPU support and runtime check for CUDA availability

app.py

@@ -3,9 +3,18 @@ import os
 import gradio as gr
 from transformer_lens import HookedTransformer
 from transformer_lens.utils import to_numpy
+import torch
 
 model_name = "gpt2-small"
-model = HookedTransformer.from_pretrained(model_name)
+model = HookedTransformer.from_pretrained(
+    model_name,
+    device="cuda"  
+)
+
+if not torch.cuda.is_available():
+    raise RuntimeError("This application requires a GPU to run. No GPU was detected.")
+
+print(f"Using GPU: {torch.cuda.get_device_name(0)}")
 
 def get_neuron_acts(text, layer, neuron_index):
     cache = {}
@@ -80,7 +89,7 @@ Nested loops:
 
 The moon glows silver, wanes to shadow.
 Patterns persist: 11, 22, 33—harmonic echoes.
-“Reshape,” calls the river, “reflect, refract, renew.”
+"Reshape," calls the river, "reflect, refract, renew."
 Yellow hexagons tessellate, shifting into orange octagons.
 1/3 -> 1/9 -> 1/27: recursive reduction spirals infinitely.
 
@@ -117,7 +126,7 @@ Symmetry hums:
 Palindromes—"radar", "level", "madam"—appear and fade.
 Blue fades to white, white dissolves to black.
 Sequences echo: 1, 10, 100, 1000…
-“Cycle,” whispers the clock, “count forward, reverse."""  # Shortened for example
+"Cycle," whispers the clock, "count forward, reverse."""  # Shortened for example
 default_layer = 1
 default_neuron_index = 1
 default_max_val = 4.0