Text Classification
Transformers
Safetensors
PyTorch
eurobert
fine-tuned
sequence-classification
binary-classification
geopolitics
multilingual
custom_code
Instructions to use Durrani95/eurobert-geopolitical-binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Durrani95/eurobert-geopolitical-binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Durrani95/eurobert-geopolitical-binary", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Durrani95/eurobert-geopolitical-binary", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("Durrani95/eurobert-geopolitical-binary", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
| ## This file was auto generated by the Azure Machine Learning Studio. Please do not remove. | |
| ## Read more about the .amlignore file here: https://docs.microsoft.com/azure/machine-learning/how-to-save-write-experiment-files#storage-limits-of-experiment-snapshots | |
| .ipynb_aml_checkpoints/ | |
| *.amltmp | |
| *.amltemp |