Create README.md

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 model processes it and returns a concise summary, allowing anyone to interact with the model without needing to write code.

README.md

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+---
+datasets:
+- abisee/cnn_dailymail
+language:
+- en
+metrics:
+- rouge
+- bleu
+- meteor
+- ter
+base_model:
+- facebook/bart-large-cnn
+pipeline_tag: summarization
+library_name: transformers
+tags:
+- code
+- Summarizer
+- BART
+- transformers
+- Gradio
+- Machine Learning
+- Natural Language Processing (NLP)
+- Deep Learning
+- Interactive Demo
+- Python
+- AI
+---