Create app.py

app.py

@@ -0,0 +1,49 @@
+"""
+## Setup and Imports
+"""
+
+# import os
+# os.environ["KERAS_BACKEND"] = "jax"
+import keras_core as keras
+import keras_nlp
+import gradio as gr
+from huggingface_hub import Repository
+
+import keras
+from keras.optimizers import Adam
+from keras.losses import SparseCategoricalCrossentropy
+import keras_nlp
+
+"""## Get the repository"""
+
+repo = Repository(
+    local_dir="title-generator-using-summary-gpt2-llm",
+    clone_from="Nageswaran/title-generator-using-summary-gpt2-llm",
+)
+
+"""## Build the model"""
+
+gpt2_lm = keras.models.load_model(
+    "title-generator-using-summary-gpt2-llm/gpt2_lm.keras"
+)
+
+title="Summary to Title"
+description="GPT2 Model for summary to title."
+
+def get_title(summary):
+    summary = summary.replace("\n", " ")
+    output = gpt2_lm.generate(f"Summary: {summary} Title:", max_length=600)
+    title = output.split("Title:")[1]
+    return title
+
+"""## Build the space and launch it"""
+
+gpt_space = gr.Interface(
+    fn=get_title,
+    inputs=gr.Textbox(label="Summary"),
+    outputs=gr.Textbox(label="Title"),
+    title=title,
+    description=description,
+)
+
+gpt_space.launch()