In a digital landscape overflowing with information, deciphering key insights from lengthy blog posts is a persistent challenge. 'SummarEase' addresses this issue by utilizing state-of-the-art Hugging Face NLP Transformers, specifically BART, I evaluated various pre-trained models such as GPT-2, BERT, and BART, identifying BART as the top performer based on the ROUGE scores (ROUGE-2 and ROUGE-L) under consideration in Blog Post Summarization. The GPT and BERT models are among the most popular extractive summarization models and the BART model is the abstractive summarization models. And, hence, I leveraged the BART model using Deep Learning techniques and implemented it as a Flask web application, 'SummarEase' that simplifies information retrieval, offers rapid, succinct summaries, enhancing content access and reducing energy consumption by 16%.