The code provided sets up a simple web-based interface for summarizing text using the facebook/bart-large-cnn model. It first installs the necessary Python libraries: transformers for using pre-trained models, and gradio for creating interactive demos. The pipeline function from transformers is then used to load the pre-trained BART model for summarization, which is specifically fine-tuned on the CNN/Daily Mail dataset for generating abstractive summaries. The function summarize_text takes an input text and uses the summarization pipeline to produce a summary, with the length of the summary constrained between 100 and 200 tokens. The do_sample=False parameter ensures deterministic results, meaning the summary is consistent with each run. Finally, a Gradio interface is created with an input textbox for users to enter their text and an output textbox to display the generated summary. The interface also includes a title and description to guide the user. When the user submits text, the mo…
