big input handle

app.py

@@ -1,17 +1,19 @@
 import streamlit as st
-from transformers import pipeline
+from transformers import pipeline, AutoTokenizer
 import pandas as pd
 
 @st.cache_resource()
 def load_model():
-    return pipeline(
+    pipe = pipeline(
         "text-classification",
         model="alxvlsv/rubert-emotions",
         tokenizer="alxvlsv/rubert-emotions",
         top_k=None
     )
+    tokenizer = AutoTokenizer.from_pretrained("alxvlsv/rubert-emotions")
+    return pipe, tokenizer
 
-model = load_model()
+model, tokenizer = load_model()
 
 label_map = {
     "LABEL_0": "admiration",
@@ -81,7 +83,9 @@ st.write("Введите текст на русском, и мы покажем,
 text_input = st.text_area("Введите текст здесь:")
 
 if text_input:
-    results = model(text_input)[0]
+    # Ограничиваем до 256 токенов
+    encoded = tokenizer(text_input, truncation=True, max_length=256, return_tensors="pt")
+    results = model(encoded)[0]
 
     # Нормализуем вероятности до 100%
     total_score = sum(r["score"] for r in results)
@@ -114,4 +118,4 @@ if text_input:
                 label_raw = item["label"]
                 label = label_map.get(label_raw, label_raw)
                 ru_label, emoji = emotion_labels.get(label, (label, "❓"))
-                st.markdown(f"{ru_label.capitalize()} {emoji} — {item['score']:.2%}")
+                st.markdown(f"{ru_label.capitalize()} {emoji} — {item['score']:.2%}")