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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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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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You can use label map with below code. |
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> |
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from huggingface_hub import hf_hub_download |
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repo_id = "JunHwi/kmhas_multilabel" |
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filename = "kmhas_dict.pickle" # μ repo_idμ μ
λ‘λν νμΌ μ΄λ¦ |
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label_dict = hf_hub_download(repo_id, filename) |
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with open(label_dict, "rb") as f: |
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label2num = pickle.load(f) |