Instructions to use yechen/bert-large-chinese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yechen/bert-large-chinese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="yechen/bert-large-chinese")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("yechen/bert-large-chinese") model = AutoModelForMaskedLM.from_pretrained("yechen/bert-large-chinese", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from yechen/bert-large-chinese: direct link, hf CLI and curl.
- Browser
- Download file 1.3 GB
-
https://huggingface.co/yechen/bert-large-chinese/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://yechen/bert-large-chinese/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/yechen/bert-large-chinese/resolve/main/flax_model.msgpack
1.3 GB
- Xet hash:
- 07f2a8cc055db8de5d61803d670e40cf877976293d9c6130ef276f9ce19fc0a1
- Size of remote file:
- 1.3 GB
- SHA256:
- c6969a19f6fc51ead61f5e4beb009eda842e63eac9906e96ad4aaaac2c114747
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