Instructions to use ckiplab/albert-base-chinese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ckiplab/albert-base-chinese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ckiplab/albert-base-chinese")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ckiplab/albert-base-chinese") model = AutoModelForMaskedLM.from_pretrained("ckiplab/albert-base-chinese") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0c525cc6dc137d0942851e7df9f05ec4ca600922a633a045e8a86a37d7888118
- Size of remote file:
- 40.3 MB
- SHA256:
- a52413db260b61d85b6ba3620d67199872da3395d6b309a40e3d455b2ca6417d
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