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import gradio as gr | |
from transformers import AutoModelForSequenceClassification, AutoTokenizer | |
import torch | |
import numpy as np | |
model_name = "dancrvlh/Language" | |
model = AutoModelForSequenceClassification.from_pretrained(model_name) | |
tokenizer = AutoTokenizer.from_pretrained(model_name) | |
mapping = { | |
2:"English", | |
3:"French", | |
4:"Portugeese", | |
5:"Russian", | |
6:"Sweedish", | |
7:"Sweedish", | |
} | |
def predict(text): | |
inputs = tokenizer(text, return_tensors="pt") | |
outputs = model(**inputs) | |
predictions = outputs.logits | |
return mapping[round(np.exp(predictions.item()))] | |
iface = gr.Interface( | |
fn=predict, | |
inputs="text", | |
outputs="text", | |
layout="vertical", | |
title="Language Detection", | |
description="This model can detect the language your text for English, French, Portugeese, Russian, Sweedish and Unknow", | |
) | |
iface.launch(share=True) |