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README.md

@@ -1,14 +1,12 @@
 ---
-title: GreekBART News24 Abstract
-emoji: ⚡
+title: GreeBART News Summarizer
+emoji: 🌐
 colorFrom: pink
-colorTo: indigo
+colorTo: gray
 sdk: gradio
-sdk_version: 5.4.0
+sdk_version: 5.1.0
 app_file: app.py
 pinned: false
-license: apache-2.0
-short_description: Greek News Summarizer
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,43 @@
+from transformers import pipeline
+import gradio as gr
+import spaces
+import os
+from threading import Thread
+from typing import Iterator
+import torch
+
+from transformers import (
+    AutoTokenizer,
+    AutoModelForSeq2SeqLM,
+    TextIteratorStreamer
+)
+device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
+tokenizer = AutoTokenizer.from_pretrained("dascim/greekbart-news24-abstract")
+model = AutoModelForSeq2SeqLM.from_pretrained("dascim/greekbart-news24-abstract")
+model.eval()
+@spaces.GPU(duration=90)
+def get_input(text) -> Iterator[str]:
+  streamer = TextIteratorStreamer(tokenizer, timeout=20.0, skip_special_tokens=True)
+  input_ids = tokenizer.encode(text, add_special_tokens=True, return_tensors='pt')
+  
+  generate_kwargs = dict(
+        input_ids=input_ids,
+        tokenizer=tokenizer,
+        device=device,
+        streamer=streamer,
+        max_new_tokens=120,
+        do_sample=False,
+        num_beams=1,
+    )
+
+  t = Thread(target=model.generate, kwargs=generate_kwargs)
+  t.start()
+
+  outputs = []
+  for text in streamer:
+      outputs.append(text)
+      yield "".join(outputs)
+  
+
+iface = gr.Interface(fn=get_input,inputs="text",outputs="text",title = "Greek News Summarizer",description="Enter your text (maximum of 512 tokens news article) to get a summary")
+iface.launch()

requirements.txt

@@ -0,0 +1,2 @@
+torch
+transformers