Fill-Mask
Transformers
PyTorch
Chinese
bert
chinese
classical chinese
literary chinese
ancient chinese
roberta
Instructions to use SIKU-BERT/sikuroberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SIKU-BERT/sikuroberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="SIKU-BERT/sikuroberta")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("SIKU-BERT/sikuroberta") model = AutoModelForMaskedLM.from_pretrained("SIKU-BERT/sikuroberta") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0a09f36d9331aca49f301ffabb6abf108c40f60c6fe77fec6d46a264c8773074
- Size of remote file:
- 436 MB
- SHA256:
- eede4853e143e741fb65cca1607c453116e172517ea31a7d9a3556d31d64e81f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.