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:
- 0ee72719bcb8b310be50028c759ebb6a9ebb9d76ac7fc5da04e46a613b5d2e44
- Size of remote file:
- 876 MB
- SHA256:
- e4896f4129b031e0c2d7e508d1368ad47f50887ad0058df5f8d642cf46a927ff
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