Update app.py

app.py

@@ -1,62 +1,61 @@
-import gradio as gr
-import torch
-from transformers import pipeline, T5TokenizerFast as T5Tokenizer
-
-MODEL_ID = 'lityops/Style-Summarizer'
-
-tokenizer = T5Tokenizer.from_pretrained(MODEL_ID)
-summarizer = pipeline(
-    "summarization",
-    model=MODEL_ID,
-    tokenizer=tokenizer,
-    device=-1
-)
-
-def generate_summary(text, style):
-    if not text or len(text.strip()) < 50:
-        return "Input must at least be 50 words long"
-
-    input_text = f"Summarize {style}: {text}"
-    input_words = len(text.split())
-
-    if style == 'Harsh':
-        max_len = int(input_words * 0.35)
-        min_len = 5
-        rep_penalty = 2.5
-        beam_size = 4
-    elif style == 'Balanced':
-        max_len = int(input_words * 0.50)
-        min_len = 20
-        rep_penalty = 1.5
-        beam_size = 4
-    else:
-        max_len = int(input_words * 0.70)
-        min_len = 50
-        rep_penalty = 1.2
-        beam_size = 4
-
-    max_len = min(max_len, 256)
-    
-    output = summarizer(
-        input_ids=input_text,
-        max_length=max_len, 
-        min_length=min_len, 
-        num_beams=beam_size,
-        repetition_penalty=rep_penalty,
-        no_repeat_ngram_size=3,
-        early_stopping=True
-    )
-    return output[0]["summary_text"]
-
-demo = gr.Interface(
-    fn=generate_summary,
-    inputs=[
-        gr.Textbox(label="Input Text", lines=10, placeholder="Paste text here..."),
-        gr.Radio(["Harsh", "Balanced", "Detailed"], label="Summary Style", value="Balanced")
-    ],
-    outputs=gr.Textbox(label="Summary"),
-    title="Style Summarizer",
-    description="A custom Flan-T5-Base model fine-tuned to generate summaries in different styles."
-)
-
+import gradio as gr
+from transformers import pipeline, T5TokenizerFast as T5Tokenizer
+
+MODEL_ID = 'lityops/Style-Summarizer'
+
+tokenizer = T5Tokenizer.from_pretrained(MODEL_ID)
+summarizer = pipeline(
+    "summarization",
+    model=MODEL_ID,
+    tokenizer=tokenizer,
+    device=-1
+)
+
+def generate_summary(text, style):
+    if not text or len(text.strip()) < 50:
+        return "Input must at least be 50 words long"
+
+    input_text = f"Summarize {style}: {text}"
+    input_words = len(text.split())
+
+    if style == 'Harsh':
+        max_len = int(input_words * 0.35)
+        min_len = 5
+        rep_penalty = 2.5
+        beam_size = 4
+    elif style == 'Balanced':
+        max_len = int(input_words * 0.50)
+        min_len = 20
+        rep_penalty = 1.5
+        beam_size = 4
+    else:
+        max_len = int(input_words * 0.70)
+        min_len = 50
+        rep_penalty = 1.2
+        beam_size = 4
+
+    max_len = min(max_len, 256)
+    
+    output = summarizer(
+        input_ids=input_text,
+        max_length=max_len, 
+        min_length=min_len, 
+        num_beams=beam_size,
+        repetition_penalty=rep_penalty,
+        no_repeat_ngram_size=3,
+        early_stopping=True
+    )
+    return output[0]["summary_text"]
+
+demo = gr.Interface(
+    fn=generate_summary,
+    inputs=[
+        gr.Textbox(label="Input Text", lines=10, placeholder="Paste text here..."),
+        gr.Radio(["Harsh", "Balanced", "Detailed"], label="Summary Style", value="Balanced")
+    ],
+    outputs=gr.Textbox(label="Summary"),
+    title="Style Summarizer",
+    description="A custom Flan-T5-Base model fine-tuned to generate summaries in different styles."
+)
+
 demo.launch()