Update app.py

app.py

@@ -1,14 +1,18 @@
 import gradio as gr
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
-tokenizer = AutoTokenizer.from_pretrained("salesken/translation-hi-en")
-model = AutoModelForSeq2SeqLM.from_pretrained("salesken/translation-hi-en")
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, AutoModelForCausalLM
+tokenizer1 = AutoTokenizer.from_pretrained("salesken/translation-hi-en")
+model1 = AutoModelForSeq2SeqLM.from_pretrained("salesken/translation-hi-en")
+tokenizer = AutoTokenizer.from_pretrained("Salesforce/codegen-16B-mono")
+model = AutoModelForCausalLM.from_pretrained("Salesforce/codegen-16B-mono")
 
 def greet(name):
     hin_snippet = name
-    inputs = tokenizer.encode(hin_snippet, return_tensors="pt",padding=True,max_length=512,truncation=True)
-    outputs = model.generate(inputs, max_length=128, num_beams=None, early_stopping=True)
-    translated = tokenizer.decode(outputs[0]).replace('<pad>',"").strip().lower()
-    return translated
+    inputs = tokenizer1.encode(hin_snippet, return_tensors="pt",padding=True,max_length=512,truncation=True)
+    outputs = model1.generate(inputs, max_length=128, num_beams=None, early_stopping=True)
+    translated = tokenizer1.decode(outputs[0]).replace('<pad>',"").strip().lower()
+    input_ids = tokenizer("# "+translated, return_tensors="pt").input_ids
+	sample = model.generate(input_ids, max_length=128)
+    return tokenizer.decode(sample[0], skip_special_tokens=True)
 
 iface = gr.Interface(fn=greet, inputs="text", outputs="text")
 iface.launch()