asd

app.py

@@ -1,40 +1,55 @@
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 import spaces
+from sentence_splitter import SentenceSplitter
 
 device = "cuda"
 
 tokenizer = AutoTokenizer.from_pretrained("NoaiGPT/777")
 model = AutoModelForSeq2SeqLM.from_pretrained("NoaiGPT/777").to(device)
 
+# Initialize the sentence splitter
+splitter = SentenceSplitter(language='en')
+
 @spaces.GPU
 def generate_title(text):
     input_ids = tokenizer(f'paraphraser: {text}', return_tensors="pt", padding="longest", truncation=True, max_length=64).input_ids.to(device)
     outputs = model.generate(
         input_ids,
-        num_beams=8,  # Increased from 4
+        num_beams=8,
         num_beam_groups=4,
-        num_return_sequences=6,  # Increased from 4
-        repetition_penalty=12.0,  # Increased from 10.0
-        diversity_penalty=4.0,  # Increased from 3.0
-        no_repeat_ngram_size=3,  # Increased from 2
-        temperature=1.1,  # Increased from 0.9
-        top_k=50,  # Added top_k sampling
-        top_p=0.95,  # Added top_p sampling
+        num_return_sequences=6,
+        repetition_penalty=12.0,
+        diversity_penalty=4.0,
+        no_repeat_ngram_size=3,
+        temperature=1.1,
+        top_k=50,
+        top_p=0.95,
         max_length=64
     )
     return tokenizer.batch_decode(outputs, skip_special_tokens=True)
 
+def process_text(text):
+    paragraphs = text.split('\n\n')
+    results = []
+    for paragraph in paragraphs:
+        sentences = splitter.split(paragraph)
+        paragraph_results = []
+        for sentence in sentences:
+            titles = generate_title(sentence)
+            paragraph_results.append(f"Original: {sentence}\nParaphrases:\n" + "\n".join(titles))
+        results.append("\n\n".join(paragraph_results))
+    return "\n\n---\n\n".join(results)
+
 def gradio_generate_title(text):
-    titles = generate_title(text)
-    return "\n\n".join(titles)
+    return process_text(text)
 
 iface = gr.Interface(
     fn=gradio_generate_title,
-    inputs=gr.Textbox(lines=5, label="Input Text"),
-    outputs=gr.Textbox(lines=10, label="Generated Titles"),
-    title="Diverse Title Generator",
-    description="Generate multiple diverse paraphrased titles from input text using NoaiGPT/777 model."
+    inputs=gr.Textbox(lines=10, label="Input Text"),
+    outputs=gr.Textbox(lines=20, label="Generated Paraphrases"),
+    title="Diverse Paraphrase Generator",
+    description="Generate multiple diverse paraphrases for each sentence in the input text using NoaiGPT/777 model."
 )
 
 iface.launch()