just multi model

app.py

@@ -6,12 +6,13 @@ modelName = "colinryan/hf-deepmoji"
 
 #distil_tokenizer = AutoTokenizer.from_pretrained(modelName)
 #distil_tokenizer.save_pretrained("./model/")
-#distil_model = DistilBertForSequenceClassification.from_pretrained(modelName, problem_type="multi_label_classification")
+distil_model = DistilBertForSequenceClassification.from_pretrained(modelName, problem_type="multi_label_classification")
 #distil_model = DistilBertForMultilabelSequenceClassification.from_pretrained("colinryan/hf-deepmoji")
 #num_labels = len(model.config.id2label)
 
 #pipeline = pipeline(task="text-classification", model=distil_model, tokenizer=distil_tokenizer)
-pipeline = pipeline(task="text-classification", model=modelName)
+pipeline = pipeline(task="text-classification", model=distil_model, tokenizer=distil_tokenizer)
+#pipeline = pipeline(task="text-classification", model=modelName)
 
 def predict(deepmoji_analysis):
     predictions = pipeline(deepmoji_analysis)