app.py

import gradio as gr
from transformers import pipeline

from huggingface_hub import get_hf_file_metadata, hf_hub_url, hub_hub_download

print(get_hf_file_metadata(hf_hub_url("eu-test/gpt2", "README.md")))
print(get_hf_file_metadata(hf_hub_url("eu-test/gpt2", "model.safetensors")))

hf_hub_download(repo_id="eu-test/gpt2", filename="64-8bits.tflite")

generator = pipeline('text-generation', model='eu-test/gpt2')

def generate(text):
    result = generator(text, max_length=30, num_return_sequences=1)
    return result[0]["generated_text"]

examples = [
    ["The Moon's orbit around Earth has"],
    ["The smooth Borealis basin in the Northern Hemisphere covers 40%"],
]

demo = gr.Interface(
    fn=generate,
    inputs=gr.inputs.Textbox(lines=5, label="Input Text"),
    outputs=gr.outputs.Textbox(label="Generated Text"),
    examples=examples
)

demo.launch()