Instructions to use hfl/chinese-macbert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hfl/chinese-macbert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hfl/chinese-macbert-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hfl/chinese-macbert-base") model = AutoModelForMaskedLM.from_pretrained("hfl/chinese-macbert-base") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- af1d505f950087c9c6a3419a0ab6e034ed3b1ebe32b4c23dbea2bb3694e6bd06
- Size of remote file:
- 412 MB
- SHA256:
- db0506d985574b80c33eec1cf13bd4c130585568753175871095ca13dbad9e23
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