Update README.md

README.md

@@ -9,44 +9,29 @@ datasets:
 metrics:
 - rouge
 ---
+# T5-Base-Sum
 
----
-## How to Get Started with the Model
+This model is a fine-tuned version of `T5` for summarization tasks. It was trained on various articles and is hosted on Hugging Face for easy access and use.
 
-Use the code below to get started with the model.
+## Model Usage
 
+Below is an example of how to load and use this model for summarization:
 
+```python
 from transformers import T5ForConditionalGeneration, T5Tokenizer
 
-# Load the model and tokenizer from Hugging Face repository
-
+# Load the model and tokenizer from Hugging Face
 model = T5ForConditionalGeneration.from_pretrained("Vijayendra/T5-Base-Sum")
 tokenizer = T5Tokenizer.from_pretrained("Vijayendra/T5-Base-Sum")
 
-# Example of a random article (can replace this with any article)
-
-random_article = """
-Videos that say approved vaccines are dangerous and cause autism, cancer or infertility are among those that will be taken down, the company said.  The policy includes the 
-termination of accounts of anti-vaccine influencers.  Tech giants have been criticised for not doing more to counter false health information on their sites.  In July, US President
- Joe Biden said social media platforms were largely responsible for people's scepticism in getting vaccinated by spreading misinformation, and appealed for them to address the 
- issue.  YouTube, which is owned by Google, said 130,000 videos were removed from its platform since last year, when it implemented a ban on content spreading misinformation 
- about Covid vaccines.  In a blog post, the company said it had seen false claims about Covid jabs "spill over into misinformation about vaccines in general". The new policy 
- covers long-approved vaccines, such as those against measles or hepatitis B.  "We're expanding our medical misinformation policies on YouTube with new guidelines on currently 
- administered vaccines that are approved and confirmed to be safe and effective by local health authorities and the WHO," the post said, referring to the World Health Organization.
+# Example of using the model for summarization
+article = """
+Videos that say approved vaccines are dangerous and cause autism, cancer or infertility are among those that will be taken down, the company said. The policy includes the
+termination of accounts of anti-vaccine influencers.
 """
-
-# Tokenize the input article
-
-inputs = tokenizer.encode("summarize: " + random_article, return_tensors="pt", max_length=512, truncation=True)
-
-# Generate summary
-
-summary_ids = model.generate(inputs, max_length=150, min_length=100, length_penalty=3.0, num_beams=7, early_stopping=False)
+inputs = tokenizer.encode("summarize: " + article, return_tensors="pt", max_length=512, truncation=True)
+summary_ids = model.generate(inputs, max_length=150, min_length=50, length_penalty=2.0, num_beams=4, early_stopping=True)
 
 # Decode and print the summary
-
 summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
-print("Summary:")
 print(summary)
----
-[More Information Needed]