Instructions to use hw2942/bert-base-chinese-finetuning-wallstreetcn-morning-news-market-overview-open-000001SH-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hw2942/bert-base-chinese-finetuning-wallstreetcn-morning-news-market-overview-open-000001SH-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hw2942/bert-base-chinese-finetuning-wallstreetcn-morning-news-market-overview-open-000001SH-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hw2942/bert-base-chinese-finetuning-wallstreetcn-morning-news-market-overview-open-000001SH-v1") model = AutoModelForSequenceClassification.from_pretrained("hw2942/bert-base-chinese-finetuning-wallstreetcn-morning-news-market-overview-open-000001SH-v1") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
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version https://git-lfs.github.com/spec/v1
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oid sha256:91a1c882b6d53459dc40d85ec09770b20defabb43a2f28360b3a8d99311175ad
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size 409100240
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