Instructions to use dlfp22/klue-bert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dlfp22/klue-bert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dlfp22/klue-bert-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dlfp22/klue-bert-base") model = AutoModelForSequenceClassification.from_pretrained("dlfp22/klue-bert-base") - Notebooks
- Google Colab
- Kaggle
Upload BertForSequenceClassification
Browse files- config.json +0 -4
- model.safetensors +1 -1
config.json
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "\ubd80\uc815",
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"1": "\uae0d\uc815"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"is_decoder": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"is_decoder": false,
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 442499040
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version https://git-lfs.github.com/spec/v1
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size 442499040
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