auto

app.py

@@ -1,23 +1,3 @@
 import gradio as gr
-from transformers import BertForSequenceClassification
-from transformers import BertTokenizer
-import torch
 
-tokenizer=BertTokenizer.from_pretrained('IDEA-CCNL/Erlangshen-Roberta-330M-Sentiment')
-model=BertForSequenceClassification.from_pretrained('IDEA-CCNL/Erlangshen-Roberta-330M-Sentiment')
-
-def predict(input_text):
-    predictions = model(torch.tensor([tokenizer.encode(input_text)]))
-    predictions=torch.nn.functional.softmax(predictions.logits,dim=-1)
-    print(predictions)
-    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()
+gr.load("models/IDEA-CCNL/Erlangshen-Roberta-330M-Sentiment").launch()