Instructions to use ckiplab/bert-base-chinese-pos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ckiplab/bert-base-chinese-pos with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ckiplab/bert-base-chinese-pos")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ckiplab/bert-base-chinese-pos") model = AutoModelForTokenClassification.from_pretrained("ckiplab/bert-base-chinese-pos") - Inference
- Notebooks
- Google Colab
- Kaggle
Specify tokenizer in config.
Browse files- config.json +1 -0
config.json
CHANGED
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@@ -145,6 +145,7 @@
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"pooler_num_fc_layers": 3,
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"pooler_size_per_head": 128,
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"pooler_type": "first_token_transform",
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"type_vocab_size": 2,
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"vocab_size": 21128
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}
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| 145 |
"pooler_num_fc_layers": 3,
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"pooler_size_per_head": 128,
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"pooler_type": "first_token_transform",
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+
"tokenizer_class": "BertTokenizerFast",
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"type_vocab_size": 2,
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"vocab_size": 21128
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}
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