Instructions to use Wilson2021/bert_cn_finetuning_model01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Wilson2021/bert_cn_finetuning_model01 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Wilson2021/bert_cn_finetuning_model01")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Wilson2021/bert_cn_finetuning_model01") model = AutoModelForMaskedLM.from_pretrained("Wilson2021/bert_cn_finetuning_model01", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Wilson2021/bert_cn_finetuning_model01: direct link, hf CLI and curl.
- Browser
- Download file 409 MB
-
https://huggingface.co/Wilson2021/bert_cn_finetuning_model01/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Wilson2021/bert_cn_finetuning_model01/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Wilson2021/bert_cn_finetuning_model01/resolve/main/pytorch_model.bin
409 MB
- Xet hash:
- 719472c931dadd7a39c7f663211b6e7342fb4fde9d32c03d1a59e2d070afc369
- Size of remote file:
- 409 MB
- SHA256:
- f13310b859b6c072d9a00361ce24fe898c7d3611e7768962cb339a3b8b4d4a5d
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