Update app.py
Browse files
app.py
CHANGED
@@ -1,4 +1,5 @@
|
|
1 |
import gradio as gr
|
|
|
2 |
|
3 |
# Load your serialized objects
|
4 |
model = joblib.load('random_forest_model_3labels2.joblib')
|
@@ -14,7 +15,7 @@ def predict(input_text):
|
|
14 |
prediction = model.predict(vectorized_text)
|
15 |
|
16 |
# If your model's output needs to be decoded (optional)
|
17 |
-
|
18 |
|
19 |
# Return the prediction (you might want to convert it into a more readable form)
|
20 |
return prediction[0] # Modify this according to your needs
|
@@ -23,7 +24,7 @@ def predict(input_text):
|
|
23 |
iface = gr.Interface(fn=predict,
|
24 |
inputs=gr.Textbox(lines=2, placeholder="Enter Text Here..."),
|
25 |
outputs="text",
|
26 |
-
description="
|
27 |
|
28 |
# Launch the app
|
29 |
iface.launch()
|
|
|
1 |
import gradio as gr
|
2 |
+
import joblib
|
3 |
|
4 |
# Load your serialized objects
|
5 |
model = joblib.load('random_forest_model_3labels2.joblib')
|
|
|
15 |
prediction = model.predict(vectorized_text)
|
16 |
|
17 |
# If your model's output needs to be decoded (optional)
|
18 |
+
decoded_prediction = encoder.inverse_transform(prediction)
|
19 |
|
20 |
# Return the prediction (you might want to convert it into a more readable form)
|
21 |
return prediction[0] # Modify this according to your needs
|
|
|
24 |
iface = gr.Interface(fn=predict,
|
25 |
inputs=gr.Textbox(lines=2, placeholder="Enter Text Here..."),
|
26 |
outputs="text",
|
27 |
+
description="Detects hate speech in text. Outputs 'Neutral or Ambiguous', 'Not Hate', or 'Offensive or Hate Speech'.")
|
28 |
|
29 |
# Launch the app
|
30 |
iface.launch()
|