Update README.md

README.md

@@ -21,15 +21,4 @@ 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
-
-## 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)
-
-```
+IMDB sentiment classification dataset for training. The model generates new movie reviews for a given prompt.