Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use cite-text-analysis/case-analysis-InLegalBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cite-text-analysis/case-analysis-InLegalBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cite-text-analysis/case-analysis-InLegalBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cite-text-analysis/case-analysis-InLegalBERT") model = AutoModelForSequenceClassification.from_pretrained("cite-text-analysis/case-analysis-InLegalBERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2c9acc96bd22d1f5e0e31eeab50580f398a4b0d80e449c1920c6b8707b1b90e9
- Size of remote file:
- 4.98 kB
- SHA256:
- 4168c8c84941deb81d05fe2d714c7e20c482e1e8b4900f8d6b307d6f8c3828dd
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