Playing with other models.

app.py

@@ -20,10 +20,11 @@ app.add_middleware(
 # "xenova/mobilebert-uncased-mnli" "typeform/mobilebert-uncased-mnli" Fast but small
 # "xenova/deberta-v3-base-tasksource-nli" Not impressed
 # "Xenova/bart-large-mnli" A bit slow
+# "Xenova/distilbert-base-uncased-mnli" "typeform/distilbert-base-uncased-mnli" Bad answers
 
-model_name = "Xenova/distilbert-base-uncased-mnli"
+model_name = "Xenova/deBERTa-v3-base-mnli"
 file_name = "onnx/model_quantized.onnx"
-tokenizer_name = "typeform/distilbert-base-uncased-mnli"
+tokenizer_name = "MoritzLaurer/DeBERTa-v3-base-mnli"
 model = ORTModelForSequenceClassification.from_pretrained(model_name, file_name=file_name)
 tokenizer = AutoTokenizer.from_pretrained(tokenizer_name, model_max_length=512)