update readme.md

README.md

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----
-license: apache-2.0
----
+---
+license: apache-2.0
+language:
+- en
+metrics:
+- rouge
+base_model: google/pegasus-cnn_dailymail
+---
+
+### Pegasus-based Text Summarization Model
+Model Name: pegsus-text-summarization
+
+### Model Description
+This model is a fine-tuned version of the Pegasus model, specifically adapted for the task of text summarization. It is trained on the SAMSum dataset, which is designed for summarizing conversations.
+
+### Usage
+This model can be used to generate concise summaries of input text, particularly for conversational text or dialogue-based inputs.
+
+### How to Use
+You can use this model with the Hugging Face transformers library. Below is an example code snippet:
+
+from transformers import PegasusForConditionalGeneration, PegasusTokenizer
+
+model_name = "ailm/pegsus-text-summarization"
+model = PegasusForConditionalGeneration.from_pretrained(model_name)
+tokenizer = PegasusTokenizer.from_pretrained(model_name)
+
+text = "Your input text here"
+tokens = tokenizer(text, truncation=True, padding="longest", return_tensors="pt")
+summary = model.generate(**tokens)
+print(tokenizer.decode(summary[0], skip_special_tokens=True))