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app.py

@@ -7,7 +7,7 @@ import torch
 
 def generate_nanogpt_text():
     model = BigramLanguageModel(vocab_size=65, n_embed=n_embed, block_size=BLOCK_SIZE, num_heads=n_head, n_layers=n_layer)
-    ckpt = torch.load(os.path.join("./nano_gpt_ckpts", "ckpt_5k_iters.pt"))
+    ckpt = torch.load(os.path.join("./nano_gpt_ckpts", "ckpt_5k_iters.pt"), map_location=torch.device('cpu'))
     model.load_state_dict(ckpt['model'])
 
     char_tokenizer = load_int_char_tokenizer(load_text())