Update app.py

app.py

@@ -1,21 +1,22 @@
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 import gradio as gr
 
-checkpoint = "Mr-Vicky-01/English-Tamil-Translator"
+checkpoint = "Mr-Vicky-01/conversational_sumarization"
 tokenizer = AutoTokenizer.from_pretrained(checkpoint)
-model = AutoModelForSeq2SeqLM.from_pretrained("Finetuned_model/")
+model = AutoModelForSeq2SeqLM.from_pretrained(checkpoint)
 
-def language_translator(text):
-    tokenized = tokenizer([text], return_tensors='pt')
-    out = model.generate(**tokenized, max_length=128)
-    return tokenizer.decode(out[0],skip_special_tokens=True)
+def generate_summary(text):
+    inputs = tokenizer([text], max_length=1024, return_tensors='pt', truncation=True)
+    summary_ids = model.generate(inputs['input_ids'], max_new_tokens=100, do_sample=False)
+    summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
+    return summary
 
-examples = [
-    ["hello everyone"],
-    ["hardwork never fails."],
-    ["A room without books is like a body without a soul."],
-    ["The Sun is approximately 4.6 billion years older than Earth."],
-]
+# examples = [
+#     ["hello everyone"],
+#     ["hardwork never fails."],
+#     ["A room without books is like a body without a soul."],
+#     ["The Sun is approximately 4.6 billion years older than Earth."],
+# ]
 
-demo = gr.Interface(fn=language_translator, inputs='text',outputs='text',title='English to Tamil Translator',examples=examples)
+demo = gr.Interface(fn=language_translator, inputs='text',outputs='text',title='Text Summarization'), #examples=examples)
 demo.launch(debug=True,share=True)