update app.py (#2)
Browse files- update app.py (fe1f1706896b2ee43521612aceaa14f3c7a19183)
Co-authored-by: kaisexX <kaisex@users.noreply.huggingface.co>
app.py
CHANGED
@@ -1,7 +1,61 @@
|
|
1 |
import gradio as gr
|
|
|
|
|
2 |
|
3 |
-
|
4 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
5 |
|
6 |
-
|
7 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
import gradio as gr
|
2 |
+
import json
|
3 |
+
from transformers import AutoTokenizer, AutoModelForSequenceClassification, TextClassificationPipeline
|
4 |
|
5 |
+
# Load Swear Words
|
6 |
+
try:
|
7 |
+
with open("swearWord.json", "r") as f:
|
8 |
+
swear_words = set(json.load(f))
|
9 |
+
print("Swear words loaded successfully.")
|
10 |
+
except Exception as e:
|
11 |
+
print(f"Failed to load swearWord.json: {e}")
|
12 |
+
swear_words = set()
|
13 |
|
14 |
+
# Load Model and Tokenizer
|
15 |
+
try:
|
16 |
+
tokenizer = AutoTokenizer.from_pretrained("eliasalbouzidi/distilbert-nsfw-text-classifier")
|
17 |
+
model = AutoModelForSequenceClassification.from_pretrained("eliasalbouzidi/distilbert-nsfw-text-classifier")
|
18 |
+
text_classifier = TextClassificationPipeline(model=model, tokenizer=tokenizer)
|
19 |
+
print("Model loaded successfully.")
|
20 |
+
except Exception as e:
|
21 |
+
print(f"Error loading model: {e}")
|
22 |
+
exit(1)
|
23 |
+
|
24 |
+
# Text Classifier Function
|
25 |
+
def textclassifier(text):
|
26 |
+
if not text.strip():
|
27 |
+
return "Empty input", 0.0
|
28 |
+
|
29 |
+
# Check for swear words
|
30 |
+
if any(word.lower() in swear_words for word in text.split()):
|
31 |
+
return "swear-word", 1.0
|
32 |
+
|
33 |
+
# Use model
|
34 |
+
try:
|
35 |
+
result = text_classifier(text)
|
36 |
+
label = result[0]["label"]
|
37 |
+
score = result[0]["score"]
|
38 |
+
|
39 |
+
# Threshold logic
|
40 |
+
threshold = 0.994
|
41 |
+
if label == "nsfw" and score < threshold:
|
42 |
+
label = "uncertain"
|
43 |
+
|
44 |
+
return label, round(score, 4)
|
45 |
+
|
46 |
+
except Exception as e:
|
47 |
+
return f"Error: {str(e)}", 0.0
|
48 |
+
|
49 |
+
# Gradio Interface
|
50 |
+
interface = gr.Interface(
|
51 |
+
fn=textclassifier,
|
52 |
+
inputs=gr.Textbox(label="Enter text"),
|
53 |
+
outputs=[
|
54 |
+
gr.Label(label="Prediction"),
|
55 |
+
gr.Number(label="Confidence Score")
|
56 |
+
],
|
57 |
+
title="Text Classifier with Swear Word Filter",
|
58 |
+
# description="First checks for swear words, then uses NSFW text classifier if no swear word is found."
|
59 |
+
)
|
60 |
+
|
61 |
+
interface.launch()
|