Update README.md

README.md

@@ -42,10 +42,11 @@ You can also use `t5-small` (77M params) available in [mini](https://huggingface
 
 ```python
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+import torch
 
-device = "cuda"
-tokenizer = AutoTokenizer.from_pretrained("Ateeqq/keywords-title-generator", token='your_token')
-model = AutoModelForSeq2SeqLM.from_pretrained("Ateeqq/keywords-title-generator", token='your_token').to(device)
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+tokenizer = AutoTokenizer.from_pretrained("Ateeqq/keywords-title-generator")
+model = AutoModelForSeq2SeqLM.from_pretrained("Ateeqq/keywords-title-generator").to(device)
 
 def generate_title(keywords):
     input_ids = tokenizer(keywords, return_tensors="pt", padding="longest", truncation=True, max_length=24).input_ids.to(device)