Instructions to use Chesscorner/bert_ru_de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Chesscorner/bert_ru_de with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Chesscorner/bert_ru_de")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Chesscorner/bert_ru_de") model = AutoModelForSequenceClassification.from_pretrained("Chesscorner/bert_ru_de", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5d3f895108b0b80e16a62a44785a09b2714e92d8378d14470b8ae6eae549df1f
- Size of remote file:
- 711 MB
- SHA256:
- c2051edc28aaea074ec75acdef654e5848d723085f5f780c2facf218296326b6
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