add files

app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
+
+
+title = "Code Compexity Predictor"
+description = "This is a space to predict complexity of Java code with [CodeParrot-Multi-Complexity](https://huggingface.co/codeparrot/codeparrot-small-multi),\
+    a multilingual model for code generation, finetuned on [CodeComplex](https://huggingface.co/datasets/codeparrot/codecomplex), a dataset for complexity prediction of Java code."
+example = [
+    ["code example 1", "nlogn"],
+    ["code example 2", "constant"]]
+
+# model to be changed to the finetuned one
+tokenizer = AutoTokenizer.from_pretrained("codeparrot/codeparrot-small-multi")
+model = AutoModelForSequenceClassification.from_pretrained("codeparrot/codeparrot-small-multi")
+
+
+def complexity_estimation(gen_prompt, topk):
+    pipe = pipeline("text-classification", model=model, tokenizer=tokenizer)
+    label = pipe(gen_prompt, do_sample=True, top_k=topk)[0]['label']
+    return label
+
+
+iface = gr.Interface(
+    fn=complexity_estimation, 
+    inputs=[
+        gr.Textbox(lines=10, label="Input code"),
+        gr.inputs.Slider(
+            minimum=1,
+            maximum=3,
+            step=1,
+            default=1,
+            label="Number of results to return",
+        ),
+    ],
+    outputs=gr.Textbox(label="Predicted complexity", lines=10),
+    examples=example,
+    layout="vertical",
+    theme="peach",
+    description=description,
+    title=title
+)
+iface.launch()

requirements.txt

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+transformers==4.19.0
+torch==1.11.0