Update README.md

README.md

@@ -85,14 +85,14 @@ tokenizer = AutoTokenizer.from_pretrained("brianknowsai/Brian-Llama-3.2-3B")
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 model.to(device)
 
-input_text = "A frame is "
+input_text = "A web3 bridge is "
 
 # Tokenize the input text
 input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to(device)
 
 # Generate output (this is typical for causal language models)
 with torch.no_grad():
-    outputs = model.generate(input_ids, max_length=50, num_return_sequences=1)
+    outputs = model.generate(input_ids, max_length=80, num_return_sequences=1)
 
 # Decode the generated tokens to text
 generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)