Initial commit

gradio_app.py

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+import gradio as gr
+from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM
+
+model_name = "t5-base"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+summarization = pipeline("summarization", model=model, tokenizer=tokenizer)
+
+def generate_summary(text):
+    summary = summarization(text, max_length=100, min_length=25, do_sample=False)
+    return summary[0]["summary_text"]
+
+input_text = gr.inputs.Textbox(lines=5, placeholder="Enter your text here...")
+output_text = gr.outputs.Textbox(label="Summary")
+
+iface = gr.Interface(
+    fn=generate_summary,
+    inputs=input_text,
+    outputs=output_text,
+    title="Text Summarization",
+    description="Enter your text and get a summary using the Hugging Face T5 model.",
+)
+
+iface.launch(share=True)  # Set share=True to get a public link to share the app.

requirements.txt

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+gradio==2.3.8
+transformers==4.12.2