Update app.py

app.py

@@ -1,32 +1,23 @@
-import os
+from transformers import pipeline
 import gradio as gr
-from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
 
-messages = [
-    {"role": "user", "content": "Who are you?"},
-]
+# Initialize the text generation pipeline
 pipe = pipeline("text-generation", model="SakanaAI/DiscoPOP-zephyr-7b-gemma")
-pipe(messages)
 
-# 日本語モデルを指定
-model_name = "SakanaAI/DiscoPOP-zephyr-7b-gemma"  # Sakana AIのモデル名を指定
-
-# トークナイザーとパイプラインの設定
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name)
-generator = pipeline('text-generation', model=model, tokenizer=tokenizer, device=-1)  # device=-1はCPUを使用する設定
-
-def generate_text(prompt, max_length):
-    result = generator(prompt, max_length=max_length, num_return_sequences=1)
+# Define a function to generate text based on user input
+def generate_text(prompt):
+    result = pipe(prompt, max_length=50, num_return_sequences=1)
     return result[0]['generated_text']
 
+# Create a Gradio interface
 iface = gr.Interface(
-    fn=generate_text,
-    inputs=[
-        gr.Textbox(label="プロンプト", placeholder="ここに日本語のプロンプトを入力してください"),
-        gr.Slider(minimum=10, maximum=200, value=50, step=1, label="最大長")
-    ],
-    outputs=gr.Textbox(label="生成されたテキスト")
+    fn=generate_text, 
+    inputs=gr.inputs.Textbox(lines=2, placeholder="Enter your prompt here..."), 
+    outputs="text",
+    title="Text Generation with DiscoPOP-zephyr-7b-gemma",
+    description="Enter a prompt and the model will generate a continuation of the text."
 )
 
-iface.launch()
+# Launch the interface
+if __name__ == "__main__":
+    iface.launch()