Update app.py

app.py

@@ -1,5 +1,7 @@
 import streamlit as st
 from transformers import pipeline
+import torch
+import matplotlib.pyplot as plt
 
 #pipe = pipeline(model="RuudVelo/dutch_news_classifier_bert_finetuned")
 #text = st.text_area('Please type/copy/paste the Dutch article')
@@ -34,10 +36,28 @@ if text:
    encoding = tokenizer(text, return_tensors="pt")
    outputs = model(**encoding)
    predictions = outputs.logits.argmax(-1)
+   probabilities = torch.nn.functional.softmax(outputs.logits, dim=-1)
+   
+   fig = plt.figure()
+   ax = fig.add_axes([0,0,1,1])
+   langs = ['Binnenland', 'Buitenland' ,'Cultuur & Media' ,'Economie' ,'Koningshuis',
+ 'Opmerkelijk' ,'Politiek', 'Regionaal nieuws', 'Tech']
+   students = probabilities[0].cpu().detach().numpy()
+   
+   ax.barh(langs,students)
+   st.pyplot(fig)
+   #plt.show()
    #out = pipe(text)
-   st.json(predictions)
+   #st.json(predictions)
    
 #encoding = tokenizer(text, return_tensors="pt")
+#import numpy as np
+
+#arr = np.random.normal(1, 1, size=100)
+#fig, ax = plt.subplots()
+#ax.hist(arr, bins=20)
+
+#st.pyplot(fig)
 
 # forward pass
 #outputs = model(**encoding)