Instructions to use hecongqing/simcse_law_bert_base_chinese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hecongqing/simcse_law_bert_base_chinese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hecongqing/simcse_law_bert_base_chinese")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hecongqing/simcse_law_bert_base_chinese") model = AutoModel.from_pretrained("hecongqing/simcse_law_bert_base_chinese") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:4cf61417b013bb8d0468a7bf9639e6bc2db82392755f723944cf6c84a90fa765
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size 409097104
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