Instructions to use hw2942/chinese-macbert-base-SSEC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hw2942/chinese-macbert-base-SSEC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hw2942/chinese-macbert-base-SSEC")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hw2942/chinese-macbert-base-SSEC") model = AutoModelForSequenceClassification.from_pretrained("hw2942/chinese-macbert-base-SSEC", device_map="auto") - 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 sha256:0ec28e679522d9840dfb5ec64b05bd4fa27a1fd47edaf1eb54a45159641a4e94
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size 409100240
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