Update app.py

app.py

@@ -2,20 +2,4 @@ import gradio as gr
 #from transformers import AutoTokenizer, AutoModel
 # import torch
 
-# Sentences we want sentence embeddings for
-sentences = ['This is an example sentence', 'Each sentence is converted']
-
-# Load model from HuggingFace Hub
-#tokenizer = AutoTokenizer.from_pretrained('sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2')
-
-tokenizer = gr.Interface.load("huggingface/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2").launch();
-
-
-# Tokenize sentences
-encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors='pt')
-
-def greet(name):
-  return "pouet"
-  
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+gr.Interface.load("huggingface/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2").launch();