Instructions to use samheym/GerCross-Encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use samheym/GerCross-Encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="samheym/GerCross-Encoder")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("samheym/GerCross-Encoder") model = AutoModelForSequenceClassification.from_pretrained("samheym/GerCross-Encoder") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a7662cef913947d6b286d08fce26cf277326db8e919b760e9180059f9ad10b0c
- Size of remote file:
- 440 MB
- SHA256:
- bc4789c66a6b26b8ecdd61d8a9e846a8bd8f3080bdd7497e788c0c7cfb18cfd5
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