Upload 2 files

app.py

@@ -0,0 +1,26 @@
+import gradio as gr
+from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification
+import torch
+
+MODEL_NAME = "kaixkhazaki/turkish-sentiment"
+device = 0 if torch.cuda.is_available() else -1
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForSequenceClassification.from_pretrained(MODEL_NAME)
+sentiment = pipeline("text-classification", model=model, tokenizer=tokenizer, return_all_scores=True, device=device)
+
+def analyze(text):
+    results = sentiment(text)[0]
+    results_sorted = sorted(results, key=lambda x: x["score"], reverse=True)
+    formatted = "\n".join([f"{r['label']}: {r['score']:.3f}" for r in results_sorted])
+    return formatted
+
+demo = gr.Interface(
+    fn=analyze,
+    inputs=gr.Textbox(lines=3, placeholder="Bir metin yazın..."),
+    outputs=gr.Textbox(label="Duygu ve Skorlar"),
+    title="Türkçe Duygu Analizi (Skorlarla)",
+    description="Her etiket için olasılık skorlarını gösterir."
+)
+
+demo.launch()

requirements.txt

@@ -0,0 +1,3 @@
+transformers>=4.44.0
+torch>=2.2.0
+gradio>=4.44.0