Text Classification
Transformers
Safetensors
German
eurobert
populism
political-speech
classification
german
Bundestag
NLP
custom_code
Instructions to use przvl/PopEuroBERT-binary-210m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use przvl/PopEuroBERT-binary-210m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="przvl/PopEuroBERT-binary-210m", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("przvl/PopEuroBERT-binary-210m", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("przvl/PopEuroBERT-binary-210m", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6084e8e05e713f62b452099185603fe3dcd44dba48bc0ccdf7b979067bbedeb7
- Size of remote file:
- 17.2 MB
- SHA256:
- c4e85f0096b756ea02d80619b9333943dc5c74fcc8c5f9de53dd0ab7705aafc3
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