Upload app.py

app.py

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+import gradio as gr
+import torch
+from transformers import (
+    AutoConfig,
+    AutoModelForSequenceClassification,
+    AutoTokenizer,
+)
+
+# ===== 基本配置 =====
+MODEL_DIR = "my-bert-model"
+MAX_LENGTH = 512
+
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+# ===== 加载模型 =====
+config = AutoConfig.from_pretrained(
+    MODEL_DIR,
+    num_labels=3,
+    finetuning_task="text-classification",
+)
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL_DIR)
+
+model = AutoModelForSequenceClassification.from_pretrained(
+    MODEL_DIR,
+    config=config
+).to(device)
+
+model.eval()
+
+# 若未定义 id2label，则自动生成
+if not hasattr(model.config, "id2label") or not model.config.id2label:
+    model.config.id2label = {i: f"LABEL_{i}" for i in range(model.config.num_labels)}
+
+# ===== 推理函数 =====
+def inference(input_text: str) -> str:
+    if not input_text or not input_text.strip():
+        return "Empty input."
+
+    inputs = tokenizer(
+        input_text,
+        max_length=MAX_LENGTH,
+        truncation=True,
+        padding="max_length",
+        return_tensors="pt",
+    )
+
+    inputs = {k: v.to(device) for k, v in inputs.items()}
+
+    with torch.no_grad():
+        outputs = model(**inputs)
+        logits = outputs.logits
+
+    predicted_class_id = torch.argmax(logits, dim=-1).item()
+    label = model.config.id2label.get(predicted_class_id, str(predicted_class_id))
+
+    return label
+
+# ===== Gradio 界面 =====
+demo = gr.Interface(
+    fn=inference,
+    inputs=gr.Textbox(
+        label="Input Text",
+        placeholder="Enter text to classify...",
+        lines=5,
+    ),
+    outputs=gr.Textbox(label="Predicted Label"),
+    examples=[
+        ["My last two weather pics from the storm on August 2nd. People packed up real fast after the temp dropped and winds picked up."],
+        ["Lying Clinton sinking! Donald Trump singing: Let's Make America Great Again!"],
+    ],
+    title="BERT-based Text Classification",
+    description="A text classification demo powered by a fine-tuned BERT model.",
+)
+
+# ===== 启动 =====
+if __name__ == "__main__":
+    demo.launch(
+        debug=False,
+        server_name="0.0.0.0",
+        server_port=7860,
+    )