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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 90ccd77242d7729890fa0430a5ccd9c353ffb227b44be043029a12795fe04435
- Size of remote file:
- 1.3 GB
- SHA256:
- 70360130cc6a273607fe22cf665dc45f4c1100078694c5c5d92e109d15104798
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