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, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 01f75bc1e7f451b83e9d79c75093e406926e2f7a7d6c36bd9993746f48cab3c5
- Size of remote file:
- 2.44 GB
- SHA256:
- 33b254b2e5b4cf1f6e54004a1b7235819231ee55d72ca58f1a7678b3e050ab20
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