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:
- 812f40dc039714dd7de70079e9a8006295b8f210fad4e73d2eee1834478fb4fd
- Size of remote file:
- 876 MB
- SHA256:
- 9e0576a9b82ef21523123f2d58a7d5d2fcdb36059d262369701873cc2f635a86
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