Update README.md

README.md

@@ -4,12 +4,15 @@ This model takes in a word as an input and splits it into syllables. I did this
 ## Calling the Model
 ```python
 from transformers import AutoTokenizer, T5ForConditionalGeneration
+
 model = T5ForConditionalGeneration.from_pretrained('imjeffhi/syllabizer')
 tokenizer = AutoTokenizer.from_pretrained('imjeffhi/syllabizer')
+
 def generate_output(word):
     tokens = tokenizer(word, return_tensors='pt')
     output = model.generate(**tokens, do_sample=False, max_length=30, early_stopping=True)[0]
     return tokenizer.decode(output, skip_special_tokens=True)
+    
 syllables = generate_output('syllabizer')
 ```
 The model returns syllables in spaced format. See output below. 
@@ -20,10 +23,13 @@ syl la biz er
 You can easily syllabize an entire sentence/paragraph and/or convert the output into a list of syllables with the following code:
 ```python
 from transformers import pipeline
+
 syllabizer_pipe = pipeline('text2text-generation', model = 'imjeffhi/syllabizer', tokenizer='imjeffhi/syllabizer')
+
 sentence = "A unit of spoken language consisting of a single uninterrupted sound formed by a vowel, diphthong, or syllabic consonant alone, or by any of these sounds preceded, followed, or surrounded by one or more consonants."
 words = sentence.split(" ")
 output = syllabizer_pipe(words, batch_size=len(words),do_sample=False, max_length=30, early_stopping=True)
+
 [{words[i]: gen_text['generated_text'].split(" ")} for i, gen_text in enumerate(output)]
 ```