Instructions to use klue/bert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use klue/bert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="klue/bert-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("klue/bert-base") model = AutoModelForMaskedLM.from_pretrained("klue/bert-base") - Inference
- Notebooks
- Google Colab
- Kaggle
File size: 425 Bytes
4782d89 e6196a5 4782d89 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | {
"architectures": ["BertForMaskedLM"],
"attention_probs_dropout_prob": 0.1,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"initializer_range": 0.02,
"intermediate_size": 3072,
"layer_norm_eps": 1e-12,
"max_position_embeddings": 512,
"model_type": "bert",
"num_attention_heads": 12,
"num_hidden_layers": 12,
"pad_token_id": 0,
"type_vocab_size": 2,
"vocab_size": 32000
}
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