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Model: hfl/chinese-bert-wwm

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hfl/chinese-bert-wwm hfl/chinese-bert-wwm
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pytorch

tf

Contributed by

hfl Joint Laboratory of HIT and iFLYTEK Research company
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How to use this model directly from the 🤗/transformers library:

			
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tokenizer = AutoTokenizer.from_pretrained("hfl/chinese-bert-wwm") model = AutoModel.from_pretrained("hfl/chinese-bert-wwm")

Config

See raw config file
attention_probs_dropout_prob: 0.1 ...
directionality: "bidi" ...
▾ finetuning_task: null ...
hidden_act: "gelu" ...
hidden_dropout_prob: 0.1 ...
hidden_size: 768 ...
initializer_range: 0.02 ...
intermediate_size: 3072 ...
is_decoder: false ...
layer_norm_eps: 1e-12 ...
max_position_embeddings: 512 ...
num_attention_heads: 12 ...
num_hidden_layers: 12 ...
num_labels: 2 ...
output_attentions: false ...
output_hidden_states: false ...
output_past: true ...
pooler_fc_size: 768 ...
pooler_num_attention_heads: 12 ...
pooler_num_fc_layers: 3 ...
pooler_size_per_head: 128 ...
pooler_type: "first_token_transform" ...
▾ pruned_heads: {} ...
torchscript: false ...
type_vocab_size: 2 ...
use_bfloat16: false ...
vocab_size: 21128 ...