Update README.md

README.md

@@ -10,6 +10,24 @@ tags:
 ---
 # chinese-text-emotion-classifier
 
+## 📚 Model Introduction
+
+This model is fine-tuned based on the [joeddav/xlm-roberta-large-xnli](https://huggingface.co/joeddav/xlm-roberta-large-xnli) model, specializing in **Chinese text emotion analysis**.  
+Through fine-tuning, the model can identify the following 8 emotion labels:
+- **Neutral tone**
+- **Concerned tone**
+- **Happy tone**
+- **Angry tone**
+- **Sad tone**
+- **Questioning tone**
+- **Surprised tone**
+- **Disgusted tone**
+
+The model is applicable to various scenarios, such as customer service emotion monitoring, social media analysis, and user feedback classification.
+
+---
+# chinese-text-emotion-classifier
+
 ## 📚 模型簡介
 本模型基於[joeddav/xlm-roberta-large-xnli](https://huggingface.co/joeddav/xlm-roberta-large-xnli) 模型進行微調，專注於 **中文語句情感分析**。  
 通過微調，模型可以識別以下 8 種情緒標籤：
@@ -25,7 +43,74 @@ tags:
 該模型適用於多種場景，例如客服情緒監控、社交媒體分析以及用戶反饋分類。
 
 ---
+## 🚀 Quick Start
+
+### Install Dependencies
+Ensure that you have installed Hugging Face's Transformers library and PyTorch:
+```bash
+pip install transformers torch
+```
+
+###Load the Model
+Use the following code to load the model and tokenizer, and perform emotion classification:
+```python
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import torch
+
+# 添加設備設定
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+# 標籤映射字典
+label_mapping = {
+    0: "平淡語氣",
+    1: "關切語調",
+    2: "開心語調",
+    3: "憤怒語調",
+    4: "悲傷語調",
+    5: "疑問語調",
+    6: "驚奇語調",
+    7: "厭惡語調"
+}
+
+def predict_emotion(text, model_path="Johnson8187/chinese-text-emotion-classifier"):
+    # 載入模型和分詞器
+    tokenizer = AutoTokenizer.from_pretrained(model_path)
+    model = AutoModelForSequenceClassification.from_pretrained(model_path).to(device)  # 移動模型到設備
+    
+    # 將文本轉換為模型輸入格式
+    inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True).to(device)  # 移動輸入到設備
+    
+    # 進行預測
+    with torch.no_grad():
+        outputs = model(**inputs)
+    
+    # 取得預測結果
+    predicted_class = torch.argmax(outputs.logits).item()
+    predicted_emotion = label_mapping[predicted_class]
+    
+    return predicted_emotion
 
+if __name__ == "__main__":
+    # 使用範例
+    test_texts = [
+        "雖然我努力了很久，但似乎總是做不到，我感到自己一無是處。",
+        "你說的那些話真的讓我很困惑，完全不知道該怎麼反應。",
+        "這世界真的是無情，為什麼每次都要給我這樣的考驗？",
+        "有時候，我只希望能有一點安靜，不要再聽到這些無聊的話題。",
+        "每次想起那段過去，我的心還是會痛，真的無法釋懷。",
+        "我從來沒有想過會有這麼大的改變，現在我覺得自己完全失控了。",
+        "我完全沒想到你會這麼做，這讓我驚訝到無法言喻。",
+        "我知道我應該更堅強，但有些時候，這種情緒真的讓我快要崩潰了。"
+    ]
+
+    for text in test_texts:
+        emotion = predict_emotion(text)
+        print(f"文本: {text}")
+        print(f"預測情緒: {emotion}\n")
+
+```
+
+---
 ## 🚀 快速開始
 
 ### 安裝依賴
@@ -95,10 +180,23 @@ if __name__ == "__main__":
 
 ---
 
+### Dataset
+- The fine-tuning dataset consists of 4,000 annotated Traditional Chinese emotion samples, covering various emotion categories to ensure the model's generalization capability in emotion classification.
+- The dataset is being prepared for public release.
+
+
 ### 數據集
 - 微調數據集來自4000個標註的繁體中文情感數據集，覆蓋了多種情緒類別，確保模型在情感分類上的泛化能力。
 - 數據集正在準備公開
 
+---
+
+🌟 Contact and Feedback
+If you encounter any issues while using this model, please contact:
+
+Email: fable8043@gmail.com
+Hugging Face Project Page: chinese-text-emotion-classifier
+
 ## 🌟 聯繫與反饋
 如果您在使用該模型時有任何問題，請聯繫：
 - 郵箱：`fable8043@gmail.com`