1st try

app.py

@@ -1,7 +1,22 @@
 import gradio as gr
+from transformers import BertForSequenceClassification
+from transformers import BertTokenizer
+import torch
 
-def greet(name):
-    return "Hello " + name + "!!"
+tokenizer=BertTokenizer.from_pretrained('IDEA-CCNL/Erlangshen-Roberta-330M-Sentiment')
+model=BertForSequenceClassification.from_pretrained('IDEA-CCNL/Erlangshen-Roberta-330M-Sentiment')
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+def predict(input_text):
+    predictions = model(torch.tensor([tokenizer.encode(text)]))
+    predictions=torch.nn.functional.softmax(predictions.logits,dim=-1)
+    return input_text, {p["label"]: p["score"] for p in predictions} 
+
+gradio_app = gr.Interface(
+    fn=predict,
+    inputs="text",
+    outputs="text",
+    title="我能做中文文本的情绪二分类",
+)
+
+if __name__ == "__main__":
+    gradio_app.launch()

requirements.txt

@@ -0,0 +1,2 @@
+transformers
+torch