Text Classification
Transformers
PyTorch
TensorBoard
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use scales-okn/docket-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use scales-okn/docket-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="scales-okn/docket-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("scales-okn/docket-classification") model = AutoModelForSequenceClassification.from_pretrained("scales-okn/docket-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 76b893ab9732ea9bbf05384d95fab37f329a33f59de097c9da20df366d45aea3
- Size of remote file:
- 1.74 GB
- SHA256:
- 6f68b2780aae23662c4ee0668e14db1c420d76522ab0975bcc249bb81de1a471
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