Update README.md

README.md

@@ -27,7 +27,7 @@ IMDB sentiment classification dataset for training. The model generates new movi
 You can use this model directly with a pipeline for text generation. Since the generation relies on some randomness, I
 set seed for reproducibility:
 ```python
->>>from transformers import pipeline, set_seed
->>>model = generation= pipeline('text-generation', model='keras-io/text-generation-miniature-gpt', tokenizer='bert-base-uncased')
->>>set_seed(20)
->>>generation("Once upon a time,", max_length=30, num_return_sequences=5)
+>>> from transformers import pipeline, set_seed
+>>> model = generation= pipeline('text-generation', model='keras-io/text-generation-miniature-gpt', tokenizer='bert-base-uncased')
+>>> set_seed(20)
+>>> generation("Once upon a time,", max_length=30, num_return_sequences=5)