Text Classification
Transformers
Safetensors
German
eurobert
fill-mask
populism
political-speech
classification
german
Bundestag
NLP
custom_code
Instructions to use przvl/PopEuroBERT-binary-610m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use przvl/PopEuroBERT-binary-610m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="przvl/PopEuroBERT-binary-610m", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("przvl/PopEuroBERT-binary-610m", trust_remote_code=True) model = AutoModelForMaskedLM.from_pretrained("przvl/PopEuroBERT-binary-610m", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2147c37f638a3e4a56071029bb4b7b97f01ce5d38cfdc724a1e8ac9b77256ac4
- Size of remote file:
- 17.2 MB
- SHA256:
- fc2befa162f4fa90daed0d884a2db4d02c2da3f6d2172dcd44b2d15259e4fb49
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