Add application file

app.py

@@ -0,0 +1,59 @@
+import gradio as gr
+import os
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+
+MODEL = "xTorch8/fine-tuned-bart"
+TOKEN = os.getenv("TOKEN")
+MAX_TOKENS = 1024
+
+model = AutoModelForSeq2SeqLM.from_pretrained(MODEL, token = TOKEN)
+tokenizer = AutoTokenizer.from_pretrained(MODEL, TOKEN)
+
+def summarize_text(text):
+    chunk_size = MAX_TOKENS * 4
+    overlap = chunk_size // 4 
+    step = chunk_size - overlap
+    chunks = [text[i:i + chunk_size] for i in range(0, len(text), step)]
+
+    summaries = []
+    for chunk in chunks:
+        inputs = tokenizer(chunk, return_tensors = "pt", truncation = True, max_length = 1024, padding = True)
+        with torch.no_grad():
+            summary_ids = model.generate(
+                **inputs,
+                max_length = 1500,
+                length_penalty = 2.0,
+                num_beams = 4,
+                early_stopping = True
+            )
+        summary = tokenizer.decode(summary_ids[0], skip_special_tokens = True)
+        summaries.append(summary)
+
+    final_text = " ".join(summaries)
+    summarization = final_text
+    if len(final_text) > MAX_TOKENS:
+        inputs = tokenizer(final_text, return_tensors = "pt", truncation = True, max_length = 1024, padding = True)
+        with torch.no_grad():
+            summary_ids = model.generate(
+                **inputs,
+                min_length = 300,
+                max_length = 1500,
+                length_penalty = 2.0,
+                num_beams = 4,
+                early_stopping = True
+            )
+        summarization = tokenizer.decode(summary_ids[0], skip_special_tokens = True)
+    else:
+        summarization = final_text 
+        
+    return summarization
+
+demo = gr.Interface(
+    fn = summarize_text,
+    inputs = gr.Textbox(lines = 20, label = "Input Text"),
+    outputs = "text",
+    title = "BART Summarizer"
+)
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

@@ -0,0 +1,3 @@
+gradio>=4.31,<5
+torch
+transformers