commit

app.py

@@ -1,7 +1,23 @@
-# app.py
-from gradio_app import iface
-from huggingface_hub import HfApi
+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.",
+)
 
-hf = HfApi()
-repo_url = hf.create_repo("test2", token="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", repo_type="spaces", exist_ok=True)
-iface.launch(debug=True, share=True, huggingface_space=repo_url)