Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use cite-text-analysis/case-analysis-bert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cite-text-analysis/case-analysis-bert-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cite-text-analysis/case-analysis-bert-base-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cite-text-analysis/case-analysis-bert-base-uncased") model = AutoModelForSequenceClassification.from_pretrained("cite-text-analysis/case-analysis-bert-base-uncased") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 33db1f3614c522d36da0cc6db5210f3fa1b575b26c7a6f782f1d03135300a8f9
- Size of remote file:
- 5.05 kB
- SHA256:
- c832ee10aa932bd0cb27acefa6d68ce6a8c58fec9dd1db56a661139c627803cd
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