Update README.md

README.md

@@ -23,12 +23,12 @@ from transformers import BertForSequenceClassification, BertTokenizer, TextClass
 model_path = "JiaqiLee/bert-agnews"
 tokenizer = BertTokenizer.from_pretrained(model_path)
 model = BertForSequenceClassification.from_pretrained(model_path, num_labels=4)
-pipeline =  TextClassificationPipeline(model=model, tokenizer=tokenizer)
+pipeline = TextClassificationPipeline(model=model, tokenizer=tokenizer)
 print(pipeline("Google scores first-day bump of 18 (USATODAY.com): USATODAY.com - Even a big first-day jump in shares of Google (GOOG) couldn't quiet debate over whether the Internet search engine's contentious auction was a hit or a flop."))
 ```
 
 ## Training data
-The training data comes HuggingFace [AGNews dataset](https://huggingface.co/datasets/ag_news). We use 90% of the `train.csv` data to train the model and the remaining 10% for evaluation.
+The training data comes from HuggingFace [AGNews dataset](https://huggingface.co/datasets/ag_news). We use 90% of the `train.csv` data to train the model and the remaining 10% for evaluation.
 
 ## Evaluation results