Instructions to use EIStakovskii/deberta-base-german_fluency with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EIStakovskii/deberta-base-german_fluency with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="EIStakovskii/deberta-base-german_fluency")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("EIStakovskii/deberta-base-german_fluency") model = AutoModelForSequenceClassification.from_pretrained("EIStakovskii/deberta-base-german_fluency", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 20d7fb78e0d16a233e6addb53e759c5674b1d1934dd67d5928099fe41626a2fa
- Size of remote file:
- 738 MB
- SHA256:
- 1d126841e4672fe05e6b4a580511d9b1c7d47325d5a502f611756181293b07ba
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