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import fasttext
from huggingface_hub import hf_hub_download
import gradio as gr
model_path = hf_hub_download(repo_id="facebook/fasttext-language-identification", filename="model.bin")
model = fasttext.load_model(model_path)
def predict(text, top):
labels, probabilities = model.predict(text, k=top)
cleaned_labels = [label.replace('__label__', '') for label in labels]
result = dict(zip(cleaned_labels, probabilities))
#result = sorted(result, key=lambda x: x[1], reverse=True)
return result
demo = gr.Interface(
fn=predict,
inputs=[
gr.Textbox(lines=1, placeholder="Text", label="Content"),
gr.Number(value=5, info='number of predictions that should be returned', minimum=1, maximum=100, label="Top"),
],
title="Language Identification Demo",
flagging_mode="never",
outputs=gr.Label(label="Result"))
demo.launch(share=True, show_api=True) |