Spaces:
Runtime error
Runtime error
create a draft of the app
Browse files
app.py
ADDED
@@ -0,0 +1,71 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import pandas as pd
|
2 |
+
import streamlit as st
|
3 |
+
import plotly.express as px
|
4 |
+
from models import NLI_MODEL_OPTIONS, NSP_MODEL_OPTIONS, METHOD_OPTIONS
|
5 |
+
|
6 |
+
st.title("Zero-shot Turkish Text Classification")
|
7 |
+
|
8 |
+
method_selection = st.radio(
|
9 |
+
"Select a zero-shot classification method.",
|
10 |
+
[
|
11 |
+
METHOD_OPTIONS["nli"],
|
12 |
+
METHOD_OPTIONS["nsp"],
|
13 |
+
],
|
14 |
+
)
|
15 |
+
|
16 |
+
if method_selection == METHOD_OPTIONS["nli"]:
|
17 |
+
model = st.selectbox(
|
18 |
+
"Select a natural language inference model.", NLI_MODEL_OPTIONS
|
19 |
+
)
|
20 |
+
if method_selection == METHOD_OPTIONS["nsp"]:
|
21 |
+
model = st.selectbox(
|
22 |
+
"Select a BERT model for next sentence prediction.", NSP_MODEL_OPTIONS
|
23 |
+
)
|
24 |
+
|
25 |
+
st.header("Configure prompts and labels")
|
26 |
+
col1, col2 = st.columns(2)
|
27 |
+
col1.subheader("Candidate labels")
|
28 |
+
labels = col1.text_area(
|
29 |
+
label="These are the labels that the model will try to predict for the given text input. Your input labels should be comma separated and meaningful.",
|
30 |
+
value="spor,dünya,siyaset,ekonomi,kültür ve sanat",
|
31 |
+
height=10,
|
32 |
+
placeholder="Enter a set of comma separated labels. (eg. spor,dünya,siyaset,ekonomi,kültür ve sanat)",
|
33 |
+
)
|
34 |
+
col2.subheader("Prompt template")
|
35 |
+
prompt_template = col2.text_area(
|
36 |
+
label="Prompt template is used to transform NLI and NSP tasks into a general-use zero-shot classifier. Models replace {} with the labels that you have given.",
|
37 |
+
value="Bu metin {} kategorisine aittir",
|
38 |
+
height=10,
|
39 |
+
)
|
40 |
+
|
41 |
+
col1.header("Make predictions")
|
42 |
+
col2.header("")
|
43 |
+
col1.text_area("", value="", placeholder="Enter some text to classify.")
|
44 |
+
col1.button("Predict")
|
45 |
+
|
46 |
+
probs = [0.86, 0.10, 0.01, 0.02, 0.01]
|
47 |
+
data = pd.DataFrame({"labels": labels.split(","), "probability": probs}).sort_values(
|
48 |
+
by="probability", ascending=False
|
49 |
+
)
|
50 |
+
chart = px.bar(
|
51 |
+
data,
|
52 |
+
x="probability",
|
53 |
+
y="labels",
|
54 |
+
color="labels",
|
55 |
+
orientation="h",
|
56 |
+
height=290,
|
57 |
+
width=500,
|
58 |
+
).update_layout(
|
59 |
+
{
|
60 |
+
"xaxis": {"title": "probability", "visible": True, "showticklabels": True},
|
61 |
+
"yaxis": {"title": None, "visible": True, "showticklabels": True},
|
62 |
+
"margin": dict(
|
63 |
+
l=10, # left
|
64 |
+
r=10, # right
|
65 |
+
t=50, # top
|
66 |
+
b=10, # bottom
|
67 |
+
),
|
68 |
+
"showlegend": False,
|
69 |
+
}
|
70 |
+
)
|
71 |
+
col2.plotly_chart(chart)
|