Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
English
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use saattrupdan/verdict-classifier-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use saattrupdan/verdict-classifier-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="saattrupdan/verdict-classifier-en")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("saattrupdan/verdict-classifier-en") model = AutoModelForSequenceClassification.from_pretrained("saattrupdan/verdict-classifier-en") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f7da960e0c44e394cc0ccd9ef396cd060db5e03b6967766504749e793f4c897b
- Size of remote file:
- 499 MB
- SHA256:
- a95a4c61deea7d0deb51d11468ecbd2275c3b4a1ffd086a3291fb63a12f76b91
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