Instructions to use cl-trier/gbert-base_sosec-topic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cl-trier/gbert-base_sosec-topic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cl-trier/gbert-base_sosec-topic")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cl-trier/gbert-base_sosec-topic") model = AutoModelForSequenceClassification.from_pretrained("cl-trier/gbert-base_sosec-topic") - Notebooks
- Google Colab
- Kaggle
Department of Computational Linguistics - University of Trier
Upload BertForSequenceClassification
5bdb547 - Xet hash:
- 41ed0c5a617bf32296083914c98c1c3d4df6e1fc8d76a71efe7dcf0071d233a2
- Size of remote file:
- 440 MB
- SHA256:
- ad97fd02ab66aeef7d4293178b36a3aaf8ef3752bf3b2eef5f88e942311943b5
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