Convert model to OpenVINO

app.py

@@ -1,9 +1,15 @@
 import gradio as gr
-from transformers import pipeline
+from optimum.intel.openvino import OVModelForSequenceClassification
+from transformers import (AutoModelForSequenceClassification, AutoTokenizer,
+                          pipeline)
 
 model_id = "juliensimon/xlm-v-base-language-id"
+ov_model = OVModelForSequenceClassification.from_pretrained(
+    model_id, from_transformers=True
+)
+tokenizer = AutoTokenizer.from_pretrained(model_id)
 
-p = pipeline("text-classification", model=model_id)
+p = pipeline("text-classification", model=ov_model, tokenizer=tokenizer)
 
 
 def process(text, top_k=5):

requirements.txt

@@ -1,2 +1,3 @@
 torch
 transformers
+optimum[openvino,nncf]