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import gradio as gr | |
from transformers import pipeline | |
classifier = pipeline("text_classification", model="Prakhar618/Gptdetect") | |
def predict(text): | |
# Convert test dataframe to Hugging Face dataset | |
test_dataset = Dataset.from_pandas(text) | |
# Apply the tokenization function to the train dataset | |
train_dataset = test_dataset.map(tokenize_function, batched=True,) | |
predictions, label_probs, _ = trainer.predict(train_dataset1) | |
y_pred = np.argmax(predictions, axis=1) | |
return y_pred | |
iface = gr.Interface(fn=predict, inputs="text", outputs="text") | |
iface.launch() |