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+ Pretrained K-mHas with multi-label model with "koelectra-v3"
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+ You can use tokenizer of this model with "monologg/koelectra-v3-base-discriminator" (https://huggingface.co/monologg/koelectra-base-v3-discriminator)
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+
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+ label maps are like this.
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+ >>>
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+ {'origin': 0,
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+ 'physical': 1,
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+ 'politics': 2,
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+ 'profanity': 3,
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+ 'age': 4,
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+ 'gender': 5,
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+ 'race': 6,
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+ 'religion': 7,
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+ 'not_hate_speech': 8}
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+
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+ You can use label map with below code.
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+ >
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+
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+ from huggingface_hub import hf_hub_download
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+
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+ repo_id = "JunHwi/kmhas_multilabel"
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+
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+ filename = "kmhas_dict.pickle" # ์œ„ repo_id์— ์—…๋กœ๋“œํ•œ ํŒŒ์ผ ์ด๋ฆ„
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+
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+ label_dict = hf_hub_download(repo_id, filename)
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+
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+ with open(label_dict, "rb") as f:
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+ label2num = pickle.load(f)