Create app.py

app.py

@@ -0,0 +1,65 @@
+import gradio as gr
+from transformers import pipeline
+
+
+def create_prompt(input_text: str, tokenizer):
+    return f"{input_text}{tokenizer.bos_token}"
+
+
+MODELS = [
+    "gpt2-sarcasm-defuser",
+    "gpt2-medium-sarcasm-defuser",
+    "bart-base-sarcasm-defuser",
+]
+MODEL_TASKS = {
+    "gpt2-sarcasm-defuser": "text-generation",
+    "gpt2-medium-sarcasm-defuser": "text-generation",
+    "bart-base-sarcasm-defuser": "text2text-generation",
+}
+model_pipe = {}
+for m in MODELS:
+    model_pipe[m] = pipeline(MODEL_TASKS[m], f"maxmarcon/{m}")
+
+
+def sarcasm_defuser(
+    text: str, model: str, max_new_tokens: int, greedy: bool, temperature: float
+):
+
+    pipe = model_pipe[model]
+
+    text = (
+        create_prompt(text, pipe.tokenizer)
+        if MODEL_TASKS[model] == "text-generation"
+        else text
+    )
+
+    model_specific_args = (
+        {"return_full_text": False} if MODEL_TASKS[model] == "text-generation" else {}
+    )
+
+    output = pipe(
+        text,
+        max_new_tokens=max_new_tokens,
+        do_sample=not greedy,
+        temperature=float(temperature),
+        **model_specific_args,
+    )
+    return output[0]["generated_text"]
+
+
+gradio_app = gr.Interface(
+    fn=sarcasm_defuser,
+    inputs=[
+        gr.Textbox(),
+        gr.Radio(MODELS, value=MODELS[0], label="Model"),
+        gr.Number(50, label="Max Tokens", precision=0),
+        gr.Checkbox(False, label="Greedy"),
+        gr.Number(1.0, label="Temperature", precision=1, step=0.1),
+    ],
+    flagging_mode="never",
+    outputs=["text"],
+    title="Sarcasm Defuser",
+)
+
+if __name__ == "__main__":
+    gradio_app.launch()