Fill-Mask
Transformers
PyTorch
Chinese
bert
chinese
classical chinese
literary chinese
ancient chinese
roberta
Instructions to use SIKU-BERT/sikubert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SIKU-BERT/sikubert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="SIKU-BERT/sikubert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("SIKU-BERT/sikubert") model = AutoModelForMaskedLM.from_pretrained("SIKU-BERT/sikubert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload bert_config.json
Browse files- bert_config.json +1 -1
bert_config.json
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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":
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}
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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": 29791
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}
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