Instructions to use Martinlabla/bert_cn_finetunning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Martinlabla/bert_cn_finetunning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Martinlabla/bert_cn_finetunning")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Martinlabla/bert_cn_finetunning") model = AutoModelForMaskedLM.from_pretrained("Martinlabla/bert_cn_finetunning") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc83866a36b434918dd5f589d6058234ff6d4224008bc83ffd2340a0a641856d
- Size of remote file:
- 409 MB
- SHA256:
- b76134d2efb8833285923581d2460a4e87b0afac712a3ba485c49a398dc07671
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