format

app.py

@@ -3,7 +3,13 @@ from transformers import AutoTokenizer, AutoModelForCausalLM
 import gradio as gr
 
 tokenizer = AutoTokenizer.from_pretrained("microsoft/phi-2", trust_remote_code=True)
-model = AutoModelForCausalLM.from_pretrained("microsoft/phi-2", torch_dtype=torch.float32, device_map="cpu", trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(
+    "microsoft/phi-2",
+    torch_dtype=torch.float32,
+    device_map="cpu",
+    trust_remote_code=True,
+)
+
 
 def generate(prompt, length):
     inputs = tokenizer(prompt, return_tensors="pt", return_attention_mask=False)
@@ -12,7 +18,19 @@ def generate(prompt, length):
     outputs = model.generate(**inputs, max_length=length)
     return tokenizer.batch_decode(outputs)[0]
 
-demo = gr.Interface(fn=generate, inputs=["text", gr.Number(value=50, label="max length",maximum=200)], outputs="text")
+
+demo = gr.Interface(
+    fn=generate,
+    inputs=[
+        gr.Text(
+            label="prompt",
+            value="Write a detailed analogy between mathematics and a lighthouse.",
+        ),
+        gr.Number(value=50, label="max length", maximum=200),
+    ],
+    outputs="text",
+)
+
 
 if __name__ == "__main__":
-   demo.launch(show_api=False)
+    demo.launch(show_api=False)