add:tqdm

RoBERTa_danmu_sentiment_analyzer.py

@@ -18,16 +18,21 @@ def load_data(file_path):
 
 # 在analyze_sentiment函数中添加模型路径处理
 def analyze_sentiment(texts):
+    """改进的情感分析函数"""
     try:
-        # 修改为优先使用打包后的模型路径
-        model_path = os.path.join(os.path.dirname(__file__), '.cache/huggingface/hub')
+        # 使用 HuggingFace 的模型
         model_name = "IDEA-CCNL/Erlangshen-Roberta-330M-Sentiment"
+        tokenizer = AutoTokenizer.from_pretrained(model_name)
+        model = AutoModelForSequenceClassification.from_pretrained(model_name)
 
-        tokenizer = AutoTokenizer.from_pretrained(model_name, cache_dir=model_path)
-        model = AutoModelForSequenceClassification.from_pretrained(model_name, cache_dir=model_path)
+        # 将模型移动到GPU
+        device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+        model = model.to(device)
 
         # 批量处理提升效率
         inputs = tokenizer(texts, padding=True, truncation=True, max_length=128, return_tensors="pt")
+        inputs = {k: v.to(device) for k, v in inputs.items()}  # 将输入数据也移动到GPU
+
         with torch.no_grad():
             outputs = model(**inputs)