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:
- 506f91e6da20e1d50cec224a92d09e490b9a975fcefdb4fff41a9908b868389a
- Size of remote file:
- 5.37 kB
- SHA256:
- 3c48b5672bb14e8245926857c466ce5febb8cea5bac75c5905fc8f8bd812f320
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