Update app.py

app.py

@@ -1,8 +1,13 @@
 import gradio as gr
+import torch
+from transformers import AutoTokenizer, AutoConfig, AutoModel, AutoModelForSequenceClassification
 
-description1 = "<h3>Demo EmotioNL</h3>\nThis demo allows you to analyse the emotion in a sentence."
+
+description_sentence = "<h3>Demo EmotioNL</h3>\nThis demo allows you to analyse the emotion in a sentence."
 description2 = "<h3>Demo EmotioNL</h3>\nThis demo allows you to analyse the emotions in a dataset.\nThe data should be in tsv-format with two named columns: the first column (id) should contain the sentence IDs, and the second column (text) should contain the actual texts. Optionally, there is a third column named 'date', which specifies the date associated with the text (e.g., tweet date). This column is necessary when the options 'emotion distribution over time' and 'peaks' are selected."
 
+inference_modelpath = "model/checkpoint-128"
+
 def what_happened(text, file_object, option_list):
     if file_object:
         output = "You uploaded a file."
@@ -35,6 +40,16 @@ def what_happened2(file_object, option_list):
     if "topics" in option_list:
         output5 = "This option was selected."
     return [output1, output2, output3, output4, output5]
+
+def inference_sentence(text):
+    tokenizer = AutoTokenizer.from_pretrained(inference_modelpath)
+    model = AutoModelForSequenceClassification.from_pretrained(inference_modelpath)
+    inputs = tokenizer(text, return_tensors="pt")
+    with torch.no_grad(): # run model
+        logits = model(**inputs).logits
+        predicted_class_id = logits.argmax().item()
+    output = model.config.id2label[predicted_class_id]
+    return output
     
 
 iface0 = gr.Interface(
@@ -52,13 +67,12 @@ iface0 = gr.Interface(
                    ],
             outputs="text")
 
-iface1 = gr.Interface(
-            fn=what_happened1,
-            description = description1,
+iface_sentence = gr.Interface(
+            fn=inference_sentence,
+            description = description_sentence,
             inputs = gr.Textbox(
                     label="Enter a sentence",
-                    lines=1,
-                    value="Your name"),
+                    lines=1),
             outputs="text")
 
 iface2 = gr.Interface(