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import gradio as gr | |
from transformers import AutoModel, pipeline | |
access_token = "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" | |
model = AutoModel.from_pretrained("EkhiAzur/RoBERTA_3", token=access_token) | |
classifier = pipeline("text-classification", model=model, max_length=512, | |
padding=True, truncation=True, batch_size=1) | |
def prozesatu(testua): | |
prediction = prozesatu.classifier(testua) | |
return f'C1:{prediction["label"]}. Probabilitatea:{prediction["score"]}' | |
gr.Interface(fn=prozesatu, inputs="text", outputs="text").launch() |