Instructions to use shibing624/songnet-base-chinese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shibing624/songnet-base-chinese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="shibing624/songnet-base-chinese")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("shibing624/songnet-base-chinese", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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---
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language:
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- zh
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tags:
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- SongNet
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- pytorch
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- zh
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- Text2Text-Generation
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license:
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widget:
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- text:
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---
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# SongNet pretrain (songnet-base-chinese) Model
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year = {2022},
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url = {https://github.com/shibing624/textgen},
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}
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```
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---
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language:
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- zh
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tags:
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- SongNet
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- pytorch
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- zh
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- Text2Text-Generation
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license: apache-2.0
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widget:
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- text: 丹枫江冷人初去
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library_name: transformers
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pipeline_tag: fill-mask
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---
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# SongNet pretrain (songnet-base-chinese) Model
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year = {2022},
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url = {https://github.com/shibing624/textgen},
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}
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```
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