Instructions to use severinsimmler/literary-german-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use severinsimmler/literary-german-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="severinsimmler/literary-german-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("severinsimmler/literary-german-bert") model = AutoModelForTokenClassification.from_pretrained("severinsimmler/literary-german-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 65640208bbae2ac91bdfafb9b51e24bdefe443cc8b374cc45b9002689890d6a9
- Size of remote file:
- 437 MB
- SHA256:
- 90bf95cb4929fa4402f096883ba4f551e210c807bb86c72498e7e10b747af6f6
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