Instructions to use zhuimengshaonian/bert-ancient-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zhuimengshaonian/bert-ancient-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="zhuimengshaonian/bert-ancient-large")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("zhuimengshaonian/bert-ancient-large") model = AutoModelForMaskedLM.from_pretrained("zhuimengshaonian/bert-ancient-large") - Notebooks
- Google Colab
- Kaggle
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Chinese Ancient BERT Model
Model description
The model's architecture is the BERT-large. We trained this model in 4 P100 about 7 days. (batch size = 6, steps = 1M)
How to use
You can use the model directly with a pipeline for text generation:
>>> from transformers import pipeline
>>> unmasker = pipeline('fill-mask', model='zhuimengshaonian/bert-ancient-base')
>>> unmasker("ζ΅·ιει±Όθ·οΌε€©ι«[MASK]ιΈι£γ")
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