Instructions to use hfl/chinese-macbert-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hfl/chinese-macbert-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hfl/chinese-macbert-large")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hfl/chinese-macbert-large") model = AutoModelForMaskedLM.from_pretrained("hfl/chinese-macbert-large") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 07bca3e7e38832ce52545fc411fb9c35d59937d4c22d8fba9e19b6cb942240b3
- Size of remote file:
- 1.31 GB
- SHA256:
- 4737fa54397e1090c49e2de6e6329e21f044c9e2476275adb9522de6b1c22e9a
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