Update app.py
Browse files
app.py
CHANGED
|
@@ -1,7 +1,7 @@
|
|
| 1 |
import gradio as gr
|
| 2 |
from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline
|
| 3 |
|
| 4 |
-
# Modeli
|
| 5 |
model = AutoModelForSequenceClassification.from_pretrained(
|
| 6 |
"savasy/bert-base-turkish-sentiment-cased"
|
| 7 |
)
|
|
@@ -21,28 +21,24 @@ def analyze(text):
|
|
| 21 |
return "🔵 POZİTİF"
|
| 22 |
elif result == "negative":
|
| 23 |
return "🔴 NEGATİF"
|
| 24 |
-
|
| 25 |
-
return "🟡 NÖTR"
|
| 26 |
|
| 27 |
-
with gr.Blocks(
|
| 28 |
gr.Markdown(
|
| 29 |
"""
|
| 30 |
# 🇹🇷 Türkçe Duygu Analizi
|
| 31 |
-
|
| 32 |
-
|
| 33 |
-
Bir cümle yaz → Model sana **POZİTİF / NEGATİF / NÖTR** sonucunu söylesin.
|
| 34 |
"""
|
| 35 |
)
|
| 36 |
|
| 37 |
-
|
| 38 |
-
|
| 39 |
-
|
| 40 |
-
|
| 41 |
-
|
| 42 |
-
|
| 43 |
-
|
| 44 |
analyze_button = gr.Button("Analiz Et")
|
| 45 |
-
|
| 46 |
output = gr.Textbox(
|
| 47 |
label="Duygu Sonucu",
|
| 48 |
interactive=False
|
|
|
|
| 1 |
import gradio as gr
|
| 2 |
from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline
|
| 3 |
|
| 4 |
+
# Modeli tek sefer yükle
|
| 5 |
model = AutoModelForSequenceClassification.from_pretrained(
|
| 6 |
"savasy/bert-base-turkish-sentiment-cased"
|
| 7 |
)
|
|
|
|
| 21 |
return "🔵 POZİTİF"
|
| 22 |
elif result == "negative":
|
| 23 |
return "🔴 NEGATİF"
|
| 24 |
+
return "🟡 NÖTR"
|
|
|
|
| 25 |
|
| 26 |
+
with gr.Blocks() as demo:
|
| 27 |
gr.Markdown(
|
| 28 |
"""
|
| 29 |
# 🇹🇷 Türkçe Duygu Analizi
|
| 30 |
+
Bir cümle yaz → Model sonucu göstersin.
|
|
|
|
|
|
|
| 31 |
"""
|
| 32 |
)
|
| 33 |
|
| 34 |
+
text_input = gr.Textbox(
|
| 35 |
+
label="Cümle",
|
| 36 |
+
placeholder="Bir cümle yazınız...",
|
| 37 |
+
lines=4
|
| 38 |
+
)
|
| 39 |
+
|
|
|
|
| 40 |
analyze_button = gr.Button("Analiz Et")
|
| 41 |
+
|
| 42 |
output = gr.Textbox(
|
| 43 |
label="Duygu Sonucu",
|
| 44 |
interactive=False
|