Update README.md

README.md

@@ -21,4 +21,13 @@ Full credits to: [fchollet](https://twitter.com/fchollet)
 This example demonstrates how to implement text generation with a miniature GPT model. The model consists of a single Transformer block with causal masking in its attention layer.
 
 ## Datasets
-IMDB sentiment classification dataset for training. The model generates new movie reviews for a given prompt
+IMDB sentiment classification dataset for training. The model generates new movie reviews for a given prompt
+
+## How to use
+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)