Fill-Mask
Transformers
PyTorch
JAX
Chinese
roberta
chinese
classical chinese
literary chinese
ancient chinese
bert
Instructions to use ethanyt/guwenbert-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ethanyt/guwenbert-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ethanyt/guwenbert-large")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ethanyt/guwenbert-large") model = AutoModelForMaskedLM.from_pretrained("ethanyt/guwenbert-large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8b955385b70e1b0b1a203c796a12117c2974798b60f4b5853189fb25cf8d4eb5
- Size of remote file:
- 1.31 GB
- SHA256:
- 10c877b231ad82e4ab0e614ebea935057ecf0b79ff90b83294820e5100c4cdd4
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