|
|
""" |
|
|
## Setup and Imports |
|
|
""" |
|
|
|
|
|
|
|
|
|
|
|
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() |
|
|
|
