Update app.py

app.py

@@ -1,18 +1,19 @@
 import gradio as gr
 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")
+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 = 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("# "+name, return_tensors="pt").input_ids
-    sample1 = model.generate(input_ids, max_length=128)
-    return tokenizer.decode(sample1[0], skip_special_tokens=True)
+    hin_snippet = name
+    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("# "+name, return_tensors="pt").input_ids
+    #sample1 = model.generate(input_ids, max_length=128)
+    #return tokenizer.decode(sample1[0], skip_special_tokens=True)
+    return translated
 
 iface = gr.Interface(fn=greet, inputs="text", outputs="text")
 iface.launch()