aaa

app.py

@@ -1,6 +1,5 @@
 import streamlit as st
 from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
-from typing import List, Dict
 import torch
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
@@ -13,7 +12,7 @@ def load_model():
     inference_model = AutoModelForSequenceClassification.from_pretrained(model_path)
     return pipeline("text-classification", model=inference_model, tokenizer=inference_tokenizer, top_k=None)
 
-def top_pct(preds: List[Dict], threshold: float = 0.95) -> List[Dict]:
+def top_pct(preds, threshold: float = 0.95):
     """Возвращает топ предсказаний, пока их суммарная вероятность не превысит threshold"""
     if not preds:
         return []
@@ -25,7 +24,7 @@ def top_pct(preds: List[Dict], threshold: float = 0.95) -> List[Dict]:
             break
     return preds[:(i+1)]
 
-def format_predictions(preds: List[Dict]) -> str:
+def format_predictions(preds) -> str:
     """Форматирует предсказания для вывода"""
     if not preds:
         return "Нет результатов"

requirements.txt

@@ -1,5 +1,4 @@
 transformers>=4.40.0
 torch>=2.2.0
 streamlit>=1.32.0
-accelerate>=0.29.0
-typing>=4.9.0
+accelerate>=0.29.0