Fill-Mask
Transformers
PyTorch
JAX
Chinese
roberta
chinese
classical chinese
literary chinese
ancient chinese
bert
Instructions to use ethanyt/guwenbert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ethanyt/guwenbert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ethanyt/guwenbert-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ethanyt/guwenbert-base") model = AutoModelForMaskedLM.from_pretrained("ethanyt/guwenbert-base") - Inference
- Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +2 -1
config.json
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"num_hidden_layers": 12,
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"pad_token_id": 1,
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"type_vocab_size": 1,
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"vocab_size": 23292
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}
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"num_hidden_layers": 12,
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"pad_token_id": 1,
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"type_vocab_size": 1,
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"vocab_size": 23292,
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"tokenizer_class": "BertTokenizer"
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}
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