Update README.md

README.md

@@ -41,13 +41,9 @@ inference:
 **How to use:**
 ```python
 from transformers import pipeline
-# 1. load the model with the huggingface `pipeline`
 genius = pipeline("text2text-generation", model='beyond/genius-large', device=0)
-# 2. provide a sketch (joint by <mask> tokens)
 sketch = "<mask> Conference on Empirical Methods <mask> submission of research papers <mask> Deep Learning <mask>"
-# 3. here we go!
-generated_text = genius(sketch, num_beams=3, do_sample=True, max_length=200)[0]['generated_text']
-print(generated_text)
+genius(sketch, num_beams=3, do_sample=True, max_length=200)[0]['generated_text']
 ```
 
 💡**GENIUS** is a powerful conditional text generation model using sketches as input, which can fill in the missing contexts for a given **sketch** (key information consisting of textual spans, phrases, or words, concatenated by mask tokens). GENIUS is pre-trained on a large-scale textual corpus with a novel *reconstruction from sketch* objective using an *extreme and selective masking* strategy, enabling it to generate diverse and high-quality texts given sketches.