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 training_args.bin from Wilson2021/bert_cn_finetuning_model01: direct link, hf CLI and curl.
- Browser
- Download file 1.21 kB
-
https://huggingface.co/Wilson2021/bert_cn_finetuning_model01/resolve/main/training_args.bin
- Command line
-
hf download hf://Wilson2021/bert_cn_finetuning_model01/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Wilson2021/bert_cn_finetuning_model01/resolve/main/training_args.bin
1.21 kB
- Xet hash:
- bf214f070b9811afe3251c1fc03ce38623a7d23764a31cb554b45b1c0ad57b30
- Size of remote file:
- 1.21 kB
- SHA256:
- 12835b28f66e0091a292e986f0fcc1b0d754a228daf623d017c7a94aaa97a658
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