Instructions to use Cube/ShijiBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cube/ShijiBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Cube/ShijiBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Cube/ShijiBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from Cube/ShijiBERT: direct link, hf CLI and curl.
- Browser
- Download file 275 Bytes
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https://huggingface.co/Cube/ShijiBERT/resolve/main/README.md
- Command line
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hf download hf://Cube/ShijiBERT/README.md
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curl -L -o README.md https://huggingface.co/Cube/ShijiBERT/resolve/main/README.md
275 Bytes
| language: | |
| - "zh" | |
| license: "apache-2.0" | |
| pipeline_tag: "fill-mask" | |
| mask_token: "[MASK]" | |
| widget: | |
| - text: "[MASK]太元中,武陵人捕鱼为业。" | |
| - text: "问征夫以前路,恨晨光之[MASK]微。" | |
| - text: "浔阳江头夜送客,枫叶[MASK]花秋瑟瑟。" | |