Instructions to use weiweishi/roc-bert-base-zh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use weiweishi/roc-bert-base-zh with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="weiweishi/roc-bert-base-zh")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("weiweishi/roc-bert-base-zh") model = AutoModelForPreTraining.from_pretrained("weiweishi/roc-bert-base-zh", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from weiweishi/roc-bert-base-zh: direct link, hf CLI and curl.
- Browser
- Download file 472 MB
-
https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/a2b838af6568e3c94d3c154b844dbb88b41c909e/pytorch_model.bin
- Command line
-
hf download hf://weiweishi/roc-bert-base-zh@a2b838af6568e3c94d3c154b844dbb88b41c909e/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/a2b838af6568e3c94d3c154b844dbb88b41c909e/pytorch_model.bin
472 MB
- Xet hash:
- 971d011a41ad25409f82f87bfe368cee20197803c1d520f0e8af5b47785eda50
- Size of remote file:
- 472 MB
- SHA256:
- f551ab7624f3bff6f023cc0263a3e93e82c044a1736ffd89845b50772c64e567
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