Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use cagrigungor/bankbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cagrigungor/bankbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cagrigungor/bankbert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cagrigungor/bankbert") model = AutoModelForSequenceClassification.from_pretrained("cagrigungor/bankbert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3f9159825a6cc75fbf2acdae059ae2a6d8e7f83c1fbd5a5bf7e1d79f7e6c0838
- Size of remote file:
- 5.3 kB
- SHA256:
- d02165f4ad6646a03ba2250eee70f4db005053684b397998638814640e2e5978
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