hey @farazk86, you almost had it right with the pipeline - as described in the docs, you also need to provide the task with the model. in this case we’re dealing with text classification (entailment), so we can use the sentiment-analysis task as follows:
from transformers import pipeline

pipe = pipeline(task="sentiment-analysis", model="roberta-large-mnli")
pipe("I like you. </s></s> I love you.") # returns [{'label': 'NEUTRAL', 'score': 0.5168218612670898}]

If you want to see how to generate the predictions using the tokenizer and model directly, I suggest checking out the MNLI task in this tutorial: https://colab.research.google.com/github/huggingface/notebooks/blob/master/examples/text_classification.ipynb 10