Update README.md

README.md

@@ -6,4 +6,35 @@ language:
 base_model:
 - google-t5/t5-small
 pipeline_tag: summarization
----
+---
+
+
+# AML Text Summarization T5 Model
+
+This is a text summarization model based on the T5-Small architecture, developed as part of the Advanced Machine Learning course at the University of Bremen.
+
+## Model Description
+
+This model is fine-tuned on the CNN/Daily Mail dataset for abstractive text summarization. It uses the T5-Small (Text-To-Text Transfer Transformer) architecture.
+
+## Usage
+
+```
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+tokenizer = AutoTokenizer.from_pretrained("s0urin/aml-text-summarization-t5")
+model = AutoModelForSeq2SeqLM.from_pretrained("s0urin/aml-text-summarization-t5")
+
+text = "Your long text here..."
+inputs = tokenizer("summarize: " + text, return_tensors="pt", max_length=512, truncation=True)
+outputs = model.generate(inputs.input_ids, max_length=150, min_length=40, length_penalty=2.0, num_beams=4, early_stopping=True)
+summary = tokenizer.decode(outputs, skip_special_tokens=True)
+
+print(summary)
+```
+
+
+## Authors
+
+- Sourin Kumar Pal
+- Jassim Hameed Ayobkhan