Token Classification
Transformers
PyTorch
Safetensors
German
bert
Archaeology
Named Entity Recognition
NER
Instructions to use alexbrandsen/bert-base-german-cased-archaeo-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alexbrandsen/bert-base-german-cased-archaeo-NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="alexbrandsen/bert-base-german-cased-archaeo-NER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("alexbrandsen/bert-base-german-cased-archaeo-NER") model = AutoModelForTokenClassification.from_pretrained("alexbrandsen/bert-base-german-cased-archaeo-NER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
bert-base-german-cased-archaeo-NER
A German BERT model for Named Entity Recognition in the Archaeology domain
This is the bert-base-german-cased-archaeo model finetuned for NER, targeting the following entities:
- Time periods (PER)
- Places (LOC)
- Artefacts (ART)
- Contexts (CON)
- Materials (MAT)
- Species (SPE)
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