Text Classification
Transformers
PyTorch
Safetensors
German
roberta
radiology
medical-imaging
chest-ct
multi-label-classification
radbert
german
ctrate
custom_code
text-embeddings-inference
Instructions to use suitch/radbert-german-ctrate-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use suitch/radbert-german-ctrate-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="suitch/radbert-german-ctrate-classifier", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("suitch/radbert-german-ctrate-classifier", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("suitch/radbert-german-ctrate-classifier", trust_remote_code=True) - 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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