Playing with models.

app.py

@@ -10,10 +10,10 @@ from optimum.onnxruntime import ORTModelForSequenceClassification
 # "Xenova/bart-large-mnli" A bit slow
 # "Xenova/distilbert-base-uncased-mnli" "typeform/distilbert-base-uncased-mnli" Bad answers
 # "Xenova/deBERTa-v3-base-mnli" "MoritzLaurer/DeBERTa-v3-base-mnli" Still a bit slow and not great answers
-model_name = "MoritzLaurer/deberta-v3-large-zeroshot-v2.0"
-file_name = "onnx/model_quantized.onnx"
-tokenizer_name = model_name
-model = ORTModelForSequenceClassification.from_pretrained(model_name) #, file_name=file_name)
+model_name = "xenova/mobilebert-uncased-mnli"
+file_name = "onnx/model.onnx"
+tokenizer_name = "typeform/mobilebert-uncased-mnli"
+model = ORTModelForSequenceClassification.from_pretrained(model_name, file_name=file_name)
 tokenizer = AutoTokenizer.from_pretrained(tokenizer_name, model_max_length=512)
 
 # file = cached_download("https://huggingface.co/" + model_name + "")