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:
- d19278907e28e00d855f08ef86fa43746e98bfbc06da4aefd314c5a475e6a2f3
- Size of remote file:
- 876 MB
- SHA256:
- 913451ea1c8f457d51fd27215063c5df87d0f1ec8b98cb959fdb4c9b4c4973b0
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