Instructions to use cduesing/bert_workforce with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cduesing/bert_workforce with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cduesing/bert_workforce")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cduesing/bert_workforce") model = AutoModelForSequenceClassification.from_pretrained("cduesing/bert_workforce") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c693633c4af03c950a5106fce2c1ee8ee452d6233bb6c47cc9b0192618d4fafc
- Size of remote file:
- 433 MB
- SHA256:
- eba0b6ea4b1531d73bc6524f1698ea54b1d695dab2f1ac63b8418da1cd3d73a3
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