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:
- 1294484322bcdecbcb70076f33f9c612b592544f5a168dd1325db3291ed49df7
- Size of remote file:
- 5.37 kB
- SHA256:
- e4d7abe90f5e3355a449311879c1fe369d8b7abc5258acb0fe3d2c66858757cd
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