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:
- 58ff8e830d927f9cb87ac2aa8cd9a323d4f6b7a34fdef0fe3213ecd299a83bda
- Size of remote file:
- 3.45 kB
- SHA256:
- 0bf2bbc73ce16844d0e1b49108fa497dce74caa70473e81700a35324ba92c18b
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