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Update app.py
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app.py
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from transformers import pipeline
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import gradio as gr
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models = {
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'devngho/ko_edu_classifier_v2_nlpai-lab_KoE5': pipeline("text-classification", model="devngho/ko_edu_classifier_v2_nlpai-lab_KoE5"),
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'devngho/ko_edu_classifier_v2_lemon-mint_LaBSE-EnKo-Nano-Preview-v0.3': pipeline("text-classification", model="devngho/ko_edu_classifier_v2_lemon-mint_LaBSE-EnKo-Nano-Preview-v0.3"),
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'devngho/ko_edu_classifier_v2_LaBSE': pipeline("text-classification", model="devngho/ko_edu_classifier_v2_LaBSE")
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}
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import gradio as gr
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def evaluate_model(input_text):
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return [model(input_text)[0]['score'] * 6 if model_name != 'devngho/ko_edu_classifier_v2_nlpai-lab_KoE5' else model('passage: ' + input_text)[0]['score'] * 6 for model_name, model in models.items()]
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from transformers import pipeline
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import gradio as gr
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import spaces
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import torch
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models = {
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'devngho/ko_edu_classifier_v2_nlpai-lab_KoE5': pipeline("text-classification", model="devngho/ko_edu_classifier_v2_nlpai-lab_KoE5", device='cuda', torch_dtype=torch.bfloat16),
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'devngho/ko_edu_classifier_v2_lemon-mint_LaBSE-EnKo-Nano-Preview-v0.3': pipeline("text-classification", model="devngho/ko_edu_classifier_v2_lemon-mint_LaBSE-EnKo-Nano-Preview-v0.3", device='cuda', torch_dtype=torch.bfloat16),
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'devngho/ko_edu_classifier_v2_LaBSE': pipeline("text-classification", model="devngho/ko_edu_classifier_v2_LaBSE", device='cuda', torch_dtype=torch.bfloat16)
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}
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import gradio as gr
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@spaces.GPU
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def evaluate_model(input_text):
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return [model(input_text)[0]['score'] * 6 if model_name != 'devngho/ko_edu_classifier_v2_nlpai-lab_KoE5' else model('passage: ' + input_text)[0]['score'] * 6 for model_name, model in models.items()]
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